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Research Aims, Objectives & Questions

The “Golden Thread” Explained Simply (+ Examples)

By: David Phair (PhD) and Alexandra Shaeffer (PhD) | June 2022

The research aims , objectives and research questions (collectively called the “golden thread”) are arguably the most important thing you need to get right when you’re crafting a research proposal , dissertation or thesis . We receive questions almost every day about this “holy trinity” of research and there’s certainly a lot of confusion out there, so we’ve crafted this post to help you navigate your way through the fog.

Overview: The Golden Thread

• What is the golden thread
• What are research aims ( examples )
• What are research objectives ( examples )
• What are research questions ( examples )
• The importance of alignment in the golden thread

What is the “golden thread”?  

The golden thread simply refers to the collective research aims , research objectives , and research questions for any given project (i.e., a dissertation, thesis, or research paper ). These three elements are bundled together because it’s extremely important that they align with each other, and that the entire research project aligns with them.

Importantly, the golden thread needs to weave its way through the entirety of any research project , from start to end. In other words, it needs to be very clearly defined right at the beginning of the project (the topic ideation and proposal stage) and it needs to inform almost every decision throughout the rest of the project. For example, your research design and methodology will be heavily influenced by the golden thread (we’ll explain this in more detail later), as well as your literature review.

The research aims, objectives and research questions (the golden thread) define the focus and scope ( the delimitations ) of your research project. In other words, they help ringfence your dissertation or thesis to a relatively narrow domain, so that you can “go deep” and really dig into a specific problem or opportunity. They also help keep you on track , as they act as a litmus test for relevance. In other words, if you’re ever unsure whether to include something in your document, simply ask yourself the question, “does this contribute toward my research aims, objectives or questions?”. If it doesn’t, chances are you can drop it.

Alright, enough of the fluffy, conceptual stuff. Let’s get down to business and look at what exactly the research aims, objectives and questions are and outline a few examples to bring these concepts to life.

Research Aims: What are they?

Simply put, the research aim(s) is a statement that reflects the broad overarching goal (s) of the research project. Research aims are fairly high-level (low resolution) as they outline the general direction of the research and what it’s trying to achieve .

Research Aims: Examples  

True to the name, research aims usually start with the wording “this research aims to…”, “this research seeks to…”, and so on. For example:

“This research aims to explore employee experiences of digital transformation in retail HR.”   “This study sets out to assess the interaction between student support and self-care on well-being in engineering graduate students”  

As you can see, these research aims provide a high-level description of what the study is about and what it seeks to achieve. They’re not hyper-specific or action-oriented, but they’re clear about what the study’s focus is and what is being investigated.

Need a helping hand?

Research Objectives: What are they?

The research objectives take the research aims and make them more practical and actionable . In other words, the research objectives showcase the steps that the researcher will take to achieve the research aims.

The research objectives need to be far more specific (higher resolution) and actionable than the research aims. In fact, it’s always a good idea to craft your research objectives using the “SMART” criteria. In other words, they should be specific, measurable, achievable, relevant and time-bound”.

Research Objectives: Examples  

Let’s look at two examples of research objectives. We’ll stick with the topic and research aims we mentioned previously.  

For the digital transformation topic:

To observe the retail HR employees throughout the digital transformation. To assess employee perceptions of digital transformation in retail HR. To identify the barriers and facilitators of digital transformation in retail HR.

And for the student wellness topic:

To determine whether student self-care predicts the well-being score of engineering graduate students. To determine whether student support predicts the well-being score of engineering students. To assess the interaction between student self-care and student support when predicting well-being in engineering graduate students.

  As you can see, these research objectives clearly align with the previously mentioned research aims and effectively translate the low-resolution aims into (comparatively) higher-resolution objectives and action points . They give the research project a clear focus and present something that resembles a research-based “to-do” list.

Research Questions: What are they?

Finally, we arrive at the all-important research questions. The research questions are, as the name suggests, the key questions that your study will seek to answer . Simply put, they are the core purpose of your dissertation, thesis, or research project. You’ll present them at the beginning of your document (either in the introduction chapter or literature review chapter) and you’ll answer them at the end of your document (typically in the discussion and conclusion chapters).  

The research questions will be the driving force throughout the research process. For example, in the literature review chapter, you’ll assess the relevance of any given resource based on whether it helps you move towards answering your research questions. Similarly, your methodology and research design will be heavily influenced by the nature of your research questions. For instance, research questions that are exploratory in nature will usually make use of a qualitative approach, whereas questions that relate to measurement or relationship testing will make use of a quantitative approach.  

Let’s look at some examples of research questions to make this more tangible.

Research Questions: Examples  

Again, we’ll stick with the research aims and research objectives we mentioned previously.  

For the digital transformation topic (which would be qualitative in nature):

How do employees perceive digital transformation in retail HR? What are the barriers and facilitators of digital transformation in retail HR?  

And for the student wellness topic (which would be quantitative in nature):

Does student self-care predict the well-being scores of engineering graduate students? Does student support predict the well-being scores of engineering students? Do student self-care and student support interact when predicting well-being in engineering graduate students?  

You’ll probably notice that there’s quite a formulaic approach to this. In other words, the research questions are basically the research objectives “converted” into question format. While that is true most of the time, it’s not always the case. For example, the first research objective for the digital transformation topic was more or less a step on the path toward the other objectives, and as such, it didn’t warrant its own research question.  

So, don’t rush your research questions and sloppily reword your objectives as questions. Carefully think about what exactly you’re trying to achieve (i.e. your research aim) and the objectives you’ve set out, then craft a set of well-aligned research questions . Also, keep in mind that this can be a somewhat iterative process , where you go back and tweak research objectives and aims to ensure tight alignment throughout the golden thread.

The importance of strong alignment 

Alignment is the keyword here and we have to stress its importance . Simply put, you need to make sure that there is a very tight alignment between all three pieces of the golden thread. If your research aims and research questions don’t align, for example, your project will be pulling in different directions and will lack focus . This is a common problem students face and can cause many headaches (and tears), so be warned.

Take the time to carefully craft your research aims, objectives and research questions before you run off down the research path. Ideally, get your research supervisor/advisor to review and comment on your golden thread before you invest significant time into your project, and certainly before you start collecting data .  

Recap: The golden thread

In this post, we unpacked the golden thread of research, consisting of the research aims , research objectives and research questions . You can jump back to any section using the links below.

As always, feel free to leave a comment below – we always love to hear from you. Also, if you’re interested in 1-on-1 support, take a look at our private coaching service here.

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

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39 Comments

Thank you very much for your great effort put. As an Undergraduate taking Demographic Research & Methodology, I’ve been trying so hard to understand clearly what is a Research Question, Research Aim and the Objectives in a research and the relationship between them etc. But as for now I’m thankful that you’ve solved my problem.

Well appreciated. This has helped me greatly in doing my dissertation.

An so delighted with this wonderful information thank you a lot.

so impressive i have benefited a lot looking forward to learn more on research.

I am very happy to have carefully gone through this well researched article.

Infact,I used to be phobia about anything research, because of my poor understanding of the concepts.

Now,I get to know that my research question is the same as my research objective(s) rephrased in question format.

I please I would need a follow up on the subject,as I intends to join the team of researchers. Thanks once again.

Thanks so much. This was really helpful.

I know you pepole have tried to break things into more understandable and easy format. And God bless you. Keep it up

i found this document so useful towards my study in research methods. thanks so much.

This is my 2nd read topic in your course and I should commend the simplified explanations of each part. I’m beginning to understand and absorb the use of each part of a dissertation/thesis. I’ll keep on reading your free course and might be able to avail the training course! Kudos!

Thank you! Better put that my lecture and helped to easily understand the basics which I feel often get brushed over when beginning dissertation work.

This is quite helpful. I like how the Golden thread has been explained and the needed alignment.

This is quite helpful. I really appreciate!

The article made it simple for researcher students to differentiate between three concepts.

Very innovative and educational in approach to conducting research.

I am very impressed with all these terminology, as I am a fresh student for post graduate, I am highly guided and I promised to continue making consultation when the need arise. Thanks a lot.

A very helpful piece. thanks, I really appreciate it .

Very well explained, and it might be helpful to many people like me.

Wish i had found this (and other) resource(s) at the beginning of my PhD journey… not in my writing up year… 😩 Anyways… just a quick question as i’m having some issues ordering my “golden thread”…. does it matter in what order you mention them? i.e., is it always first aims, then objectives, and finally the questions? or can you first mention the research questions and then the aims and objectives?

Thank you for a very simple explanation that builds upon the concepts in a very logical manner. Just prior to this, I read the research hypothesis article, which was equally very good. This met my primary objective.

My secondary objective was to understand the difference between research questions and research hypothesis, and in which context to use which one. However, I am still not clear on this. Can you kindly please guide?

In research, a research question is a clear and specific inquiry that the researcher wants to answer, while a research hypothesis is a tentative statement or prediction about the relationship between variables or the expected outcome of the study. Research questions are broader and guide the overall study, while hypotheses are specific and testable statements used in quantitative research. Research questions identify the problem, while hypotheses provide a focus for testing in the study.

Exactly what I need in this research journey, I look forward to more of your coaching videos.

This helped a lot. Thanks so much for the effort put into explaining it.

What data source in writing dissertation/Thesis requires?

What is data source covers when writing dessertation/thesis

This is quite useful thanks

I’m excited and thankful. I got so much value which will help me progress in my thesis.

where are the locations of the reserch statement, research objective and research question in a reserach paper? Can you write an ouline that defines their places in the researh paper?

Very helpful and important tips on Aims, Objectives and Questions.

Thank you so much for making research aim, research objectives and research question so clear. This will be helpful to me as i continue with my thesis.

Thanks much for this content. I learned a lot. And I am inspired to learn more. I am still struggling with my preparation for dissertation outline/proposal. But I consistently follow contents and tutorials and the new FB of GRAD Coach. Hope to really become confident in writing my dissertation and successfully defend it.

As a researcher and lecturer, I find splitting research goals into research aims, objectives, and questions is unnecessarily bureaucratic and confusing for students. For most biomedical research projects, including ‘real research’, 1-3 research questions will suffice (numbers may differ by discipline).

Awesome! Very important resources and presented in an informative way to easily understand the golden thread. Indeed, thank you so much.

Well explained

The blog article on research aims, objectives, and questions by Grad Coach is a clear and insightful guide that aligns with my experiences in academic research. The article effectively breaks down the often complex concepts of research aims and objectives, providing a straightforward and accessible explanation. Drawing from my own research endeavors, I appreciate the practical tips offered, such as the need for specificity and clarity when formulating research questions. The article serves as a valuable resource for students and researchers, offering a concise roadmap for crafting well-defined research goals and objectives. Whether you’re a novice or an experienced researcher, this article provides practical insights that contribute to the foundational aspects of a successful research endeavor.

A great thanks for you. it is really amazing explanation. I grasp a lot and one step up to research knowledge.

I really found these tips helpful. Thank you very much Grad Coach.

I found this article helpful. Thanks for sharing this.

thank you so much, the explanation and examples are really helpful

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Module 1: Introduction: What is Research?

Learning Objectives

By the end of this module, you will be able to:

• Explain how the scientific method is used to develop new knowledge
• Describe why it is important to follow a research plan

The Scientific Method consists of observing the world around you and creating a  hypothesis  about relationships in the world. A hypothesis is an informed and educated prediction or explanation about something. Part of the research process involves testing the  hypothesis , and then examining the results of these tests as they relate to both the hypothesis and the world around you. When a researcher forms a hypothesis, this acts like a map through the research study. It tells the researcher which factors are important to study and how they might be related to each other or caused by a  manipulation  that the researcher introduces (e.g. a program, treatment or change in the environment). With this map, the researcher can interpret the information he/she collects and can make sound conclusions about the results.

Research can be done with human beings, animals, plants, other organisms and inorganic matter. When research is done with human beings and animals, it must follow specific rules about the treatment of humans and animals that have been created by the U.S. Federal Government. This ensures that humans and animals are treated with dignity and respect, and that the research causes minimal harm.

No matter what topic is being studied, the value of the research depends on how well it is designed and done. Therefore, one of the most important considerations in doing good research is to follow the design or plan that is developed by an experienced researcher who is called the  Principal Investigator  (PI). The PI is in charge of all aspects of the research and creates what is called a  protocol  (the research plan) that all people doing the research must follow. By doing so, the PI and the public can be sure that the results of the research are real and useful to other scientists.

Module 1: Discussion Questions

• How is a hypothesis like a road map?
• Who is ultimately responsible for the design and conduct of a research study?
• How does following the research protocol contribute to informing public health practices?

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Home » Research Objectives – Types, Examples and Writing Guide

Research Objectives – Types, Examples and Writing Guide

Table of Contents

Research Objectives

Research objectives refer to the specific goals or aims of a research study. They provide a clear and concise description of what the researcher hopes to achieve by conducting the research . The objectives are typically based on the research questions and hypotheses formulated at the beginning of the study and are used to guide the research process.

Types of Research Objectives

Here are the different types of research objectives in research:

• Exploratory Objectives: These objectives are used to explore a topic, issue, or phenomenon that has not been studied in-depth before. The aim of exploratory research is to gain a better understanding of the subject matter and generate new ideas and hypotheses .
• Descriptive Objectives: These objectives aim to describe the characteristics, features, or attributes of a particular population, group, or phenomenon. Descriptive research answers the “what” questions and provides a snapshot of the subject matter.
• Explanatory Objectives : These objectives aim to explain the relationships between variables or factors. Explanatory research seeks to identify the cause-and-effect relationships between different phenomena.
• Predictive Objectives: These objectives aim to predict future events or outcomes based on existing data or trends. Predictive research uses statistical models to forecast future trends or outcomes.
• Evaluative Objectives : These objectives aim to evaluate the effectiveness or impact of a program, intervention, or policy. Evaluative research seeks to assess the outcomes or results of a particular intervention or program.
• Prescriptive Objectives: These objectives aim to provide recommendations or solutions to a particular problem or issue. Prescriptive research identifies the best course of action based on the results of the study.
• Diagnostic Objectives : These objectives aim to identify the causes or factors contributing to a particular problem or issue. Diagnostic research seeks to uncover the underlying reasons for a particular phenomenon.
• Comparative Objectives: These objectives aim to compare two or more groups, populations, or phenomena to identify similarities and differences. Comparative research is used to determine which group or approach is more effective or has better outcomes.
• Historical Objectives: These objectives aim to examine past events, trends, or phenomena to gain a better understanding of their significance and impact. Historical research uses archival data, documents, and records to study past events.
• Ethnographic Objectives : These objectives aim to understand the culture, beliefs, and practices of a particular group or community. Ethnographic research involves immersive fieldwork and observation to gain an insider’s perspective of the group being studied.
• Action-oriented Objectives: These objectives aim to bring about social or organizational change. Action-oriented research seeks to identify practical solutions to social problems and to promote positive change in society.
• Conceptual Objectives: These objectives aim to develop new theories, models, or frameworks to explain a particular phenomenon or set of phenomena. Conceptual research seeks to provide a deeper understanding of the subject matter by developing new theoretical perspectives.
• Methodological Objectives: These objectives aim to develop and improve research methods and techniques. Methodological research seeks to advance the field of research by improving the validity, reliability, and accuracy of research methods and tools.
• Theoretical Objectives : These objectives aim to test and refine existing theories or to develop new theoretical perspectives. Theoretical research seeks to advance the field of knowledge by testing and refining existing theories or by developing new theoretical frameworks.
• Measurement Objectives : These objectives aim to develop and validate measurement instruments, such as surveys, questionnaires, and tests. Measurement research seeks to improve the quality and reliability of data collection and analysis by developing and testing new measurement tools.
• Design Objectives : These objectives aim to develop and refine research designs, such as experimental, quasi-experimental, and observational designs. Design research seeks to improve the quality and validity of research by developing and testing new research designs.
• Sampling Objectives: These objectives aim to develop and refine sampling techniques, such as probability and non-probability sampling methods. Sampling research seeks to improve the representativeness and generalizability of research findings by developing and testing new sampling techniques.

How to Write Research Objectives

Writing clear and concise research objectives is an important part of any research project, as it helps to guide the study and ensure that it is focused and relevant. Here are some steps to follow when writing research objectives:

• Identify the research problem : Before you can write research objectives, you need to identify the research problem you are trying to address. This should be a clear and specific problem that can be addressed through research.
• Define the research questions : Based on the research problem, define the research questions you want to answer. These questions should be specific and should guide the research process.
• Identify the variables : Identify the key variables that you will be studying in your research. These are the factors that you will be measuring, manipulating, or analyzing to answer your research questions.
• Write specific objectives: Write specific, measurable objectives that will help you answer your research questions. These objectives should be clear and concise and should indicate what you hope to achieve through your research.
• Use the SMART criteria: To ensure that your research objectives are well-defined and achievable, use the SMART criteria. This means that your objectives should be Specific, Measurable, Achievable, Relevant, and Time-bound.
• Revise and refine: Once you have written your research objectives, revise and refine them to ensure that they are clear, concise, and achievable. Make sure that they align with your research questions and variables, and that they will help you answer your research problem.

Example of Research Objectives

Examples of research objectives Could be:

Research Objectives for the topic of “The Impact of Artificial Intelligence on Employment”:

• To investigate the effects of the adoption of AI on employment trends across various industries and occupations.
• To explore the potential for AI to create new job opportunities and transform existing roles in the workforce.
• To examine the social and economic implications of the widespread use of AI for employment, including issues such as income inequality and access to education and training.
• To identify the skills and competencies that will be required for individuals to thrive in an AI-driven workplace, and to explore the role of education and training in developing these skills.
• To evaluate the ethical and legal considerations surrounding the use of AI for employment, including issues such as bias, privacy, and the responsibility of employers and policymakers to protect workers’ rights.

When to Write Research Objectives

• At the beginning of a research project : Research objectives should be identified and written down before starting a research project. This helps to ensure that the project is focused and that data collection and analysis efforts are aligned with the intended purpose of the research.
• When refining research questions: Writing research objectives can help to clarify and refine research questions. Objectives provide a more concrete and specific framework for addressing research questions, which can improve the overall quality and direction of a research project.
• After conducting a literature review : Conducting a literature review can help to identify gaps in knowledge and areas that require further research. Writing research objectives can help to define and focus the research effort in these areas.
• When developing a research proposal: Research objectives are an important component of a research proposal. They help to articulate the purpose and scope of the research, and provide a clear and concise summary of the expected outcomes and contributions of the research.
• When seeking funding for research: Funding agencies often require a detailed description of research objectives as part of a funding proposal. Writing clear and specific research objectives can help to demonstrate the significance and potential impact of a research project, and increase the chances of securing funding.
• When designing a research study : Research objectives guide the design and implementation of a research study. They help to identify the appropriate research methods, sampling strategies, data collection and analysis techniques, and other relevant aspects of the study design.
• When communicating research findings: Research objectives provide a clear and concise summary of the main research questions and outcomes. They are often included in research reports and publications, and can help to ensure that the research findings are communicated effectively and accurately to a wide range of audiences.
• When evaluating research outcomes : Research objectives provide a basis for evaluating the success of a research project. They help to measure the degree to which research questions have been answered and the extent to which research outcomes have been achieved.
• When conducting research in a team : Writing research objectives can facilitate communication and collaboration within a research team. Objectives provide a shared understanding of the research purpose and goals, and can help to ensure that team members are working towards a common objective.

Purpose of Research Objectives

Some of the main purposes of research objectives include:

• To clarify the research question or problem : Research objectives help to define the specific aspects of the research question or problem that the study aims to address. This makes it easier to design a study that is focused and relevant.
• To guide the research design: Research objectives help to determine the research design, including the research methods, data collection techniques, and sampling strategy. This ensures that the study is structured and efficient.
• To measure progress : Research objectives provide a way to measure progress throughout the research process. They help the researcher to evaluate whether they are on track and meeting their goals.
• To communicate the research goals : Research objectives provide a clear and concise description of the research goals. This helps to communicate the purpose of the study to other researchers, stakeholders, and the general public.

Advantages of Research Objectives

Here are some advantages of having well-defined research objectives:

• Focus : Research objectives help to focus the research effort on specific areas of inquiry. By identifying clear research questions, the researcher can narrow down the scope of the study and avoid getting sidetracked by irrelevant information.
• Clarity : Clearly stated research objectives provide a roadmap for the research study. They provide a clear direction for the research, making it easier for the researcher to stay on track and achieve their goals.
• Measurability : Well-defined research objectives provide measurable outcomes that can be used to evaluate the success of the research project. This helps to ensure that the research is effective and that the research goals are achieved.
• Feasibility : Research objectives help to ensure that the research project is feasible. By clearly defining the research goals, the researcher can identify the resources required to achieve those goals and determine whether those resources are available.
• Relevance : Research objectives help to ensure that the research study is relevant and meaningful. By identifying specific research questions, the researcher can ensure that the study addresses important issues and contributes to the existing body of knowledge.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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• insurgent learning
• convivial research
• facilitation
• direct action
• guerrilla media

Objects of Study

Often left unspecified and mostly assumed or taken for granted, an object of study is one of the most fundamental technologies of any investigative process. Drawing from the work of Jorge Gonzalez, we approach an object of study as a socially constructed research tool that works best when explicit, transparent, and strategic. A comprehensive object of study should organize at least nine components: Title, Area of Interest, Topic, Research Question, Practical Problem, Research Problem, Techniques, Information Produced, and Glossary. The complete object of study should manage a number of obligations required of any investigation. Thus, an object of study frames a research question, articulates a claim, formulates co-generated information, facilitates techniques to co-produce knowledge, and proposes a system(s) of information. A successful object of study manages the epistemological, theoretical, and methodological contributions of the research.

A collectively articulated object of study should be treated as emergent, evolving with greater strategic focus and clarity through the dynamic interaction of a community of struggle organizing itself into an emergent research collective. An object of study is less likely to objectify a community of struggle when it is collectively generated through convivial processes. In a convivial approach, we insist that an object of study should be collectively determined and that its articulation should reflect the specific interests of a community struggle.

Convivial Research Guides

Object of study workshop handout

Interactive Object of Study

Objects of Study web page

Strategic Texts

Bell Hooks, “Feminist Scholarship: Ethical Issues,” in Talking Back: Thinking Feminist, Thinking Black(Boston: Southend Press, 1989): 42-48;

Marta Malo de Molina, “Common Notions;”

Linda Tuhiwai Smith, “Imperialism, History, Writing, Theory,” in Decolonizing Methodologies: Research and Indigenous Peoples (London: Zed Books, 2002): 19-41;

Nate Holdren and Sebastian Touza, “Introduction to Colectivo Situaciones,” ephemera 5:4 (November 2005): 595-601;

Colectivo Situaciones, “Something More on Research Militancy: Footnotes on Procedures and (In)Decisions,”ephemera 5:4 (November 2005): 602-614;

Colectivo Situaciones, “On the Researcher-Militant;”

Mario Barrera and Geralda Vialpando, eds., Action Research: In Defense of the Barrio (Los Angeles: Aztlan Publications, 1974.

• Aims and Objectives – A Guide for Academic Writing
• Doing a PhD

One of the most important aspects of a thesis, dissertation or research paper is the correct formulation of the aims and objectives. This is because your aims and objectives will establish the scope, depth and direction that your research will ultimately take. An effective set of aims and objectives will give your research focus and your reader clarity, with your aims indicating what is to be achieved, and your objectives indicating how it will be achieved.

Introduction

There is no getting away from the importance of the aims and objectives in determining the success of your research project. Unfortunately, however, it is an aspect that many students struggle with, and ultimately end up doing poorly. Given their importance, if you suspect that there is even the smallest possibility that you belong to this group of students, we strongly recommend you read this page in full.

This page describes what research aims and objectives are, how they differ from each other, how to write them correctly, and the common mistakes students make and how to avoid them. An example of a good aim and objectives from a past thesis has also been deconstructed to help your understanding.

What Are Aims and Objectives?

Research aims.

A research aim describes the main goal or the overarching purpose of your research project.

In doing so, it acts as a focal point for your research and provides your readers with clarity as to what your study is all about. Because of this, research aims are almost always located within its own subsection under the introduction section of a research document, regardless of whether it’s a thesis , a dissertation, or a research paper .

A research aim is usually formulated as a broad statement of the main goal of the research and can range in length from a single sentence to a short paragraph. Although the exact format may vary according to preference, they should all describe why your research is needed (i.e. the context), what it sets out to accomplish (the actual aim) and, briefly, how it intends to accomplish it (overview of your objectives).

To give an example, we have extracted the following research aim from a real PhD thesis:

Example of a Research Aim

The role of diametrical cup deformation as a factor to unsatisfactory implant performance has not been widely reported. The aim of this thesis was to gain an understanding of the diametrical deformation behaviour of acetabular cups and shells following impaction into the reamed acetabulum. The influence of a range of factors on deformation was investigated to ascertain if cup and shell deformation may be high enough to potentially contribute to early failure and high wear rates in metal-on-metal implants.

Note: Extracted with permission from thesis titled “T he Impact And Deformation Of Press-Fit Metal Acetabular Components ” produced by Dr H Hothi of previously Queen Mary University of London.

Research Objectives

Where a research aim specifies what your study will answer, research objectives specify how your study will answer it.

They divide your research aim into several smaller parts, each of which represents a key section of your research project. As a result, almost all research objectives take the form of a numbered list, with each item usually receiving its own chapter in a dissertation or thesis.

Following the example of the research aim shared above, here are it’s real research objectives as an example:

Example of a Research Objective

• Develop finite element models using explicit dynamics to mimic mallet blows during cup/shell insertion, initially using simplified experimentally validated foam models to represent the acetabulum.
• Investigate the number, velocity and position of impacts needed to insert a cup.
• Determine the relationship between the size of interference between the cup and cavity and deformation for different cup types.
• Investigate the influence of non-uniform cup support and varying the orientation of the component in the cavity on deformation.
• Examine the influence of errors during reaming of the acetabulum which introduce ovality to the cavity.
• Determine the relationship between changes in the geometry of the component and deformation for different cup designs.
• Develop three dimensional pelvis models with non-uniform bone material properties from a range of patients with varying bone quality.
• Use the key parameters that influence deformation, as identified in the foam models to determine the range of deformations that may occur clinically using the anatomic models and if these deformations are clinically significant.

It’s worth noting that researchers sometimes use research questions instead of research objectives, or in other cases both. From a high-level perspective, research questions and research objectives make the same statements, but just in different formats.

Taking the first three research objectives as an example, they can be restructured into research questions as follows:

Restructuring Research Objectives as Research Questions

• Can finite element models using simplified experimentally validated foam models to represent the acetabulum together with explicit dynamics be used to mimic mallet blows during cup/shell insertion?
• What is the number, velocity and position of impacts needed to insert a cup?
• What is the relationship between the size of interference between the cup and cavity and deformation for different cup types?

Difference Between Aims and Objectives

Hopefully the above explanations make clear the differences between aims and objectives, but to clarify:

• The research aim focus on what the research project is intended to achieve; research objectives focus on how the aim will be achieved.
• Research aims are relatively broad; research objectives are specific.
• Research aims focus on a project’s long-term outcomes; research objectives focus on its immediate, short-term outcomes.
• A research aim can be written in a single sentence or short paragraph; research objectives should be written as a numbered list.

How to Write Aims and Objectives

Before we discuss how to write a clear set of research aims and objectives, we should make it clear that there is no single way they must be written. Each researcher will approach their aims and objectives slightly differently, and often your supervisor will influence the formulation of yours on the basis of their own preferences.

Regardless, there are some basic principles that you should observe for good practice; these principles are described below.

Your aim should be made up of three parts that answer the below questions:

• Why is this research required?
• What is this research about?
• How are you going to do it?

The easiest way to achieve this would be to address each question in its own sentence, although it does not matter whether you combine them or write multiple sentences for each, the key is to address each one.

The first question, why , provides context to your research project, the second question, what , describes the aim of your research, and the last question, how , acts as an introduction to your objectives which will immediately follow.

Scroll through the image set below to see the ‘why, what and how’ associated with our research aim example.

Note: Your research aims need not be limited to one. Some individuals per to define one broad ‘overarching aim’ of a project and then adopt two or three specific research aims for their thesis or dissertation. Remember, however, that in order for your assessors to consider your research project complete, you will need to prove you have fulfilled all of the aims you set out to achieve. Therefore, while having more than one research aim is not necessarily disadvantageous, consider whether a single overarching one will do.

Research Objectives

Each of your research objectives should be SMART :

• Specific – is there any ambiguity in the action you are going to undertake, or is it focused and well-defined?
• Measurable – how will you measure progress and determine when you have achieved the action?
• Achievable – do you have the support, resources and facilities required to carry out the action?
• Relevant – is the action essential to the achievement of your research aim?
• Timebound – can you realistically complete the action in the available time alongside your other research tasks?

In addition to being SMART, your research objectives should start with a verb that helps communicate your intent. Common research verbs include:

Table of Research Verbs to Use in Aims and Objectives

Last, format your objectives into a numbered list. This is because when you write your thesis or dissertation, you will at times need to make reference to a specific research objective; structuring your research objectives in a numbered list will provide a clear way of doing this.

To bring all this together, let’s compare the first research objective in the previous example with the above guidance:

Checking Research Objective Example Against Recommended Approach

Research Objective:

1. Develop finite element models using explicit dynamics to mimic mallet blows during cup/shell insertion, initially using simplified experimentally validated foam models to represent the acetabulum.

Checking Against Recommended Approach:

Q: Is it specific? A: Yes, it is clear what the student intends to do (produce a finite element model), why they intend to do it (mimic cup/shell blows) and their parameters have been well-defined ( using simplified experimentally validated foam models to represent the acetabulum ).

Q: Is it measurable? A: Yes, it is clear that the research objective will be achieved once the finite element model is complete.

Q: Is it achievable? A: Yes, provided the student has access to a computer lab, modelling software and laboratory data.

Q: Is it relevant? A: Yes, mimicking impacts to a cup/shell is fundamental to the overall aim of understanding how they deform when impacted upon.

Q: Is it timebound? A: Yes, it is possible to create a limited-scope finite element model in a relatively short time, especially if you already have experience in modelling.

Q: Does it start with a verb? A: Yes, it starts with ‘develop’, which makes the intent of the objective immediately clear.

Q: Is it a numbered list? A: Yes, it is the first research objective in a list of eight.

Mistakes in Writing Research Aims and Objectives

1. making your research aim too broad.

Having a research aim too broad becomes very difficult to achieve. Normally, this occurs when a student develops their research aim before they have a good understanding of what they want to research. Remember that at the end of your project and during your viva defence , you will have to prove that you have achieved your research aims; if they are too broad, this will be an almost impossible task. In the early stages of your research project, your priority should be to narrow your study to a specific area. A good way to do this is to take the time to study existing literature, question their current approaches, findings and limitations, and consider whether there are any recurring gaps that could be investigated .

Note: Achieving a set of aims does not necessarily mean proving or disproving a theory or hypothesis, even if your research aim was to, but having done enough work to provide a useful and original insight into the principles that underlie your research aim.

2. Making Your Research Objectives Too Ambitious

Be realistic about what you can achieve in the time you have available. It is natural to want to set ambitious research objectives that require sophisticated data collection and analysis, but only completing this with six months before the end of your PhD registration period is not a worthwhile trade-off.

3. Formulating Repetitive Research Objectives

Each research objective should have its own purpose and distinct measurable outcome. To this effect, a common mistake is to form research objectives which have large amounts of overlap. This makes it difficult to determine when an objective is truly complete, and also presents challenges in estimating the duration of objectives when creating your project timeline. It also makes it difficult to structure your thesis into unique chapters, making it more challenging for you to write and for your audience to read.

Fortunately, this oversight can be easily avoided by using SMART objectives.

Hopefully, you now have a good idea of how to create an effective set of aims and objectives for your research project, whether it be a thesis, dissertation or research paper. While it may be tempting to dive directly into your research, spending time on getting your aims and objectives right will give your research clear direction. This won’t only reduce the likelihood of problems arising later down the line, but will also lead to a more thorough and coherent research project.

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• Research is an Activity and a Subject of Study: A Proposed Metaconcept and Its Practical Application (75619 views)
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Research Is an Activity and a Subject of Study: A Proposed Metaconcept and Its Practical Application

Allison Hosier *

Information literacy instruction based on the ACRL Information Literacy Competency Standards for Higher Education tends to focus on basic research skills. However, research is not just a skill but also a subject of study. The ACRL Framework for Information Literacy for Higher Education opens the door to integrating the study of research into information literacy instruction via its acknowledgement of the contextual nature of research. This article introduces the metaconcept that research is both an activity and a subject of study. The application of this metaconcept in core LIS literature is discussed and a model for incorporating the study of research into information literacy instruction is suggested.

Introduction

Studies have shown that students’ confidence in their research skills often does not match their proficiency with those skills. 1 Students seem to believe that their facility with search engines is sufficient for any research-related task they may be faced with. In believing this, what students fail to realize is that while the information-seeking skills they have developed are certainly valuable in some situations, they are less so in others.

Instructors of composition courses face a similar dilemma. Students believe that writing is nothing more than a basic skill and often fail to appreciate the importance of rhetorical context to the writing process. In an effort to resolve this, instructors help students familiarize themselves with different genres of writing via the study of writing itself. As a result, students may begin to recognize that basic skills are not enough to meet the expectations for writing in every context. The most successful student writers are ones who are able to recognize themselves as novices in some of these contexts. 2 These student writers will also begin to see that writing is not just an activity but also a subject of study. 3

Students who learn about research through information literacy instruction may not have the opportunity to experience a similar epiphany about the research process. This is because common models of information literacy instruction are primarily skills-based with a particular focus on application. There is little if any time to devote to teaching students about the contextual nature of research or how to study a research product for evidence of conventions related to these contexts.

If information literacy instruction is typically skills-based, it is likely because the ACRL Information Literacy Competency Standards for Higher Education (the Standards ) is a skills-based document, as are similar documents that have shaped how information literacy has been taught until now. The Standards guidelines in particular fail to address the contextual nature of research in a meaningful way, thus limiting opportunities to introduce this important concept in the classroom.

The advent of the ACRL Framework for Information Literacy for Higher Education (the Framework ) marks a shift from skills-based thinking about information literacy to concept-based thinking. Because of this shift, information literacy instructors now have the option to expand their teaching beyond the application of basic research skills. The Framework ’s attention to context in particular can be used to create a model of instruction that involves the study of research in addition to the application of research skills. In this way, students will better recognize that research, like writing, is both an activity and a subject of study.

The purpose of this article is threefold. The first is to propose the metaconcept that research is both an activity and a subject of study. This metaconcept has long been present in the literature in the library and information science field but has been largely absent from information literacy instruction. The second goal of this study is dto discuss how the influence of the Standards led to the skills-based model of information literacy instruction while suggesting that the Framework ’s attention to context provides a path for reshaping such instruction around the study of research. Third, a model for integrating this metaconcept into information literacy instruction will be presented.

These ideas were initially inspired by Adler-Kassner and Wardle’s edited volume Naming What We Know: Threshold Concepts of Writing Studies . Just as Adler-Kassner and Wardle and their collaborators aimed to articulate what writing studies experts know about their subject to improve conversations with students and other nonexperts, the application of the ideas in the present study can lead to better discussions about information literacy with those who in the past may not have fully understood its value.

Defining Research

Before getting to the heart of this paper’s argument, it may be helpful to first establish more clearly what, exactly, is meant by “research.”

In their “Policy for Protection of Human Research Subjects,” the Office for Human Research Protections defines research as a systematic investigation intended to contribute to generalizable knowledge. 4 Institutional Review Boards commonly use this definition to guide researchers applying for approval to pursue research involving human subjects.

The Standards also portrays research as an investigation, one that likely involves the use of library resources. The prescribed steps for the research process include the identification of a gap in knowledge, the identification and evaluation of relevant sources, and the ethical use of those sources. 5

In the Framework , research is alluded to as a “reflective discovery of information” in the expanded definition of information literacy. 6 This journey of reflective discovery is intended to lead to the creation of new knowledge.

Information-seeking is a concept related closely to research that takes into consideration contexts beyond the scientific and academic ones that are the primary concern of the above definitions. Wilson describes information-seeking as a behavior that “arises as a consequence of a need perceived by an information user who…makes demands upon formal or informal information sources or services, which result in success or failure to find relevant information.” 7

It is necessary to define research broadly in a discussion of research as both an activity and a subject of study, because the study of research can take many forms and context is always a consideration. For this reason, the understanding of research in this paper will encompass the following:

• Research is any formal or informal process that is undertaken to fill a gap in knowledge, build on existing knowledge, or create new knowledge.
• Goals of research include but are not limited to answering a research question, testing a hypothesis, or satisfying curiosity.
• Research involves investigation of some kind. This investigation may be formal, such as an exhaustive literature review or the careful implementation of the scientific method, or it may be informal, such as a brief Google search. More formal research investigations may be qualitative or quantitative in nature.
• The research process is often iterative rather than linear.
• The results of research may be captured in a research product or a set of research products. The products of research can take many forms, including but not limited to: formally published research studies, dissertations, conference proceedings, creative works, presentations, speeches, news and magazine articles, and blog posts.
• Research products often include evidence of research in some way, whether it is a list of citations, a detailed description of methodology, a quote from an interview subject, a list of acknowledgements, a verbal allusion to a source of information (as in a speech), or contextual links (as in an online blog post).

Research envisioned through an information literacy lens is often academic in nature. This type of research will be referred to as “academic research” throughout this paper. Table 1 outlines additional terms that will be used to refer to different types of research where necessary. This is not intended as a definitive list of research genres but rather a guide that will serve to clarify certain points. Note that some types of research may overlap with others.

Research Is a Subject of Study

A study of research is one in which the products or processes of research are analyzed to better understand some aspect of research itself. This is most directly seen in studies that observe actual research behaviors or evaluate specific research products. The study of research also has an influence on other areas of inquiry. Context is often key to studies of research.

The study of research is most prevalent in literature found in the library and information science (LIS) field. However, it also has relevant applications in other fields. This section will first summarize areas of inquiry directly and indirectly related to the study of research that can be found in LIS literature. A few relevant examples from the related field of writing studies will also be mentioned. Brief consideration will then be given to a relevant example from the field of psychology.

The Study of Research in Library and Information Science

Researchers in library and information science study the processes and products of research to improve systems and services, to understand how those systems and services are used, to analyze collections, to measure the impact of research-related instruction, to trace the development of a research topic over time, and more. These areas of inquiry are studied in a variety of contexts using a range of methods and populations. The study of research is relevant to virtually every specialization in library and information science. It is not an exaggeration to say that if you open any of the core journals in this field, such as those identified in a 2014 study by Nixon, 8 you are likely to find at least one article that is concerned directly or indirectly with the study of research in some way, shape, or form.

The study of research is a theme that has long been present in LIS literature but can be difficult to locate because until now it has not generally been named as such. The metaconcept introduced here gives us a novel lens through which to view our work and begin to articulate what we know about research as both an activity and a subject of study in a new way. When this lens is applied to content analyses and literature reviews, which are fairly common in LIS literature 9 and are themselves an example of the study of research, these works can serve as a valuable proxy for identifying topics related to the study of research in our field. An analysis by Tuomaala, Jarvelin, & Vakkari from 2014 may be most useful in this respect for the present discussion. 10 The breakdown of topics and subtopics the authors created for their study is specific enough to begin to see shades of the research-as-subject metaconcept. In their analysis, the authors found that information seeking, which includes subtopics such as information use and information management, accounted for 12.3 percent of the LIS literature in 2005, the most recent year considered for the study. The study of research also has applications related to studies of information storage and retrieval, a separate topic that includes subtopics such as cataloging and the testing of retrieval systems. More than 30 percent of the articles published that year related to this topic. Other potentially relevant areas from Tuomaala, Jarvelin, and Vakkari’s study include research on user education (1.7%), citation patterns (6.5%), and webometrics (2.9%).

What does the study of research in LIS look like? For one, it is often concerned with context. Researchers seek to gain important insights into how different populations seek or use information in different contexts. Some of the populations studied in recent issues of core LIS journals include disadvantaged adolescents, Catholic clergy, linguists, and poultry farmers, to name just a few. 11 Contexts of interest found in recent literature include not just academic or scholarly ones 12 but also personal, as in studies of everyday life information seeking, 13 and professional, as in studies of how information is accessed and used in various workplace environments. 14 Those who study the products of research may be interested in understanding how researchers cite data, what common themes can be found in the research on a particular subject, or how the content of one type of research product might distinguish it from another type of research product. 15 In all of these cases, context matters to the researcher.

Context also matters to those whose work may be informed by the study of research though research itself is not the direct object of study. For example, the work of collection management researchers must be informed at least in part by how a particular population uses the collection in question. 16 Usability studies may be primarily concerned with issues of design, but the researcher must also take into account the context in which the resource being tested will actually be used. 17 A study of a library’s physical space must include some consideration for the research and information-seeking activities that users conduct in that space, which will be different depending on details such as the type and size of the library as well as the population it serves. 18 Researchers who create algorithms or implement other methods to improve the effectiveness of information retrieval systems must have some understanding of the needs and behaviors of the system’s front-end users. 19 Though the examples cited are all from recent literature, they represent areas of inquiry that have developed over a long period of time.

In the past, the study of academic research as conducted by students has been of particular concern to those who teach information literacy. Leckie, for example, comments on how typical research assignments reflect an expert approach to research that may be inaccessible to novice student researchers. 20 Information literacy instruction is also often informed by studies that establish an understanding of students’ research behavior, including their method of strategic satisficing, 21 why they prefer certain resources and tools over others, 22 and why their choices do not always match expert expectations of quality and reliability. 23 Understanding gaps between the research skills librarians teach and the ones that are actually used in the workplace, as in Head, Van Hoeck, Eschler, and Fullerton, is another area of inquiry that has gained importance over time. 24

Among these studies of the products and processes of academic research are arguments for teaching students about the contextual nature of research. Fister advocates for creating a better awareness of the rhetorical aspects of research, 25 an idea that was later put into action by Davidson and Crateau. 26 Simmons proposes applying genre theory and critical information literacy to research instruction so that librarians can position themselves as discourse mediators, studying and teaching the conventions of research in different disciplines as anthropologists study and teach the practices of different cultures. 27 Harris makes a similar argument: “Before we make assumptions about how to assist communities of learning, we may also need to define and navigate the social, political, and cultural characteristics of that community.” 28

The study of research touches nearly every aspect of the library and information science field, in one form or another. But, as Faix points out, experts in other fields also take part in scholarly conversations about research. 29 This includes related fields such as writing studies, where authors like Brent and North approach the study of research from a composition perspective. 30 However, the study of research is also relevant to researchers in more scientific fields, which are often considered outside the scope of information literacy instruction. Though this paper focuses primarily on information literacy instruction, the overall argument is that such instruction would be more effective if it involved the study of research to help students appreciate the contextual nature of the research process. This means expanding our thinking about research beyond the library-based academic notions we have favored so far. For this reason, a relevant example of the study of research in psychology is provided in the next section.

The Study of Replicability and Reproducibility in Psychology

The methods, goals, and motivations of scientific research are considered to be distinct from the ones described by documents such as the Standards and the Framework . That this is the case serves as further evidence in support of the importance of context to the research process. However, scientific researchers have also been known to turn inward and examine the processes and products of research as it is represented in their fields.

In the field of psychology, the work done as part of the Reproducibility Project is particularly relevant to the present discussion. As part of this project, a team of researchers attempted to replicate the results of 100 psychological studies. 31 Their findings led them to create a set of recommendations for how to improve the research and publication process in their field to better promote replicability. One of these recommendations was to teach students to study research publications in their fields to evaluate the evidence used and learn to see potential methodological flaws.

The findings of this project inspired a number of responses. Some researchers studied the methods undertaken by those who worked on the project and used these analyses to question or criticize the results. 32 Others turned to conversations about whether replicability and reproducibility should be goals of psychological research in the first place. 33 There are also studies, 34 published since then, that seek to establish whether there are methods that can be used to improve the replicability of a study and others 35 that recommend new approaches to evaluating replicability itself. A similar study to investigate the reproducibility of cancer biology research is also being undertaken. 36

From these discussions, it becomes clear that research is not just an activity but also a subject of study for researchers in LIS and other fields. This metaconcept has important connections to the contextual nature of research. Both ideas are essential to learning about research in a meaningful way. Despite this, information literacy instruction tends to be generally skills-based with little or no discussion of these ideas. The reason for this may be that, for many, models of information literacy instruction have been built around the Standards , a document that places priority on teaching research skills over research-related concepts.

The Importance of Context: Limitations of the Standards and New Opportunities

As stated earlier, the Standards is a skills-based document. When considering the historical context of this document, its focus on the activity of research makes sense. Information literacy had developed over time from a job skill to one that was more closely related to research. Meanwhile, bibliographic instruction had also shifted from the original concept-based approaches to ones that focused more on teaching students basic access skills. 37 The Standards simply reflected these ways of thinking.

The Standards was also developed at a time when academic librarians were seeking to stake a place for themselves in the missions of their institutions, which had become more closely tied to the employability of their graduates. 38 For such institutions, learning outcomes became the favored way of gauging the success of a particular program. One of the Standards ’ stated goals is to provide measurable learning outcomes for information literacy. 39 To be measurable, learning outcomes must be based on what can be observed. It is much easier to measure the development of skills than it is to measure changes in a student’s worldview.

The limitations of the Standards have been well documented over time. 40 One of the main shortcomings of the Standards has always been in its failure to acknowledge the importance of context to the research process. More accurately, the Standards assume a single research context: that of library-based academic research. The closest the document comes to referencing the contextual nature of research is the occasional gesture toward discipline-specific research, which is still a highly academic notion (see table 2). Despite the aspiration of the Standards toward transferability, 41 research studies that have tested this idea tend to have mixed results. 42 In other words, despite its stated intentions, what the document is really doing is, as Mark points out, reflecting a tendency in the academy to measure expertise by one’s ability to adopt the conventions of academia. 43

Because the Standards does not adequately take into account the contextual nature of research, neither does Standards -based information literacy instruction. Instead, such instruction focuses primarily if not exclusively on teaching students the basic skills associated with library-based academic research. We know this because influential tools created to standardize the assessment of information literacy learning, such as the Information Literacy VALUE rubrics and the learning goals suggested by the Middle States Commission of Higher Education, reflect it. 44 We also know this because studies of syllabi for credit-bearing information literacy courses show that the most common topics taught as part of these courses are skills-based. 45

The influence of the Standards has had a noticeable effect on the way librarians think about teaching information literacy. When asked by Hofer, Townsend, and Brunetti about the most common “stuck places” students encountered when learning about research, the answers given by the librarians who participated in the study were concerned almost exclusively with academic research skills. 46 One place where a more contextual view of research shows through is in the respondents’ stated desire to help students better understand how the process of information creation might differ from one discipline to another.

The Standards has also had an effect on how information literacy is perceived by those outside the library field. When Gullikson asked nonlibrary faculty at what academic level they would expect students to have achieved individual learning outcomes from the Standards , the majority of those who responded indicated that they would expect students to have mastered these skills in the early part of their careers in higher education, if not before. 47 Standards- based information literacy, in the eyes of nonlibrarians, is at best seen as what Norgaard calls “a mere look up skill.” 48

The Standards provides no path to introducing students to the contextual nature of research. Because of this, the idea that research is both an activity and a subject of study became lost in our information literacy instruction and our thinking about information literacy instruction despite the fact that it remained a prevalent theme in our professional literature. In insisting on the importance of context to the research process, 49 the Framework gives us a way to change our thinking and our instruction.

Each of the Framework ’s six frames is infused with implicit and explicit references to the contextual nature of research (see table 3). In fact, the only frame in which the word “context” does not appear in one form or another is “Research as Inquiry,” which still manages to highlight the importance of distinguishing between processes of inquiry intended to meet different needs.

Of course, the Framework, like the Standards , is also a product of ACRL and so, as Foasberg points out, its contexts of interest are still primarily academic in nature. 50 No doubt research is currently underway to test the transferability of the Framework . In the meantime, it is not difficult to imagine how the six frames could apply to nonacademic forms of research. For example, negotiating a meaning from varying perspectives, as described in the “Scholarship as Conversation” frame, is as of much concern to those conducting personal, professional, or creative research as it is to those conducting academic research. Those who follow the investigative steps of the scientific method can likely find relevance in the idea of “Research as Inquiry.”

It may be true that not every threshold concept will apply to every research context. For some, that might be seen as a shortcoming of the present argument. However, it is worth remembering that the Framework is intended to be a flexible document, making it clear that there is room for more threshold concepts than those identified in the original version. 51 Further, in establishing a set of threshold concepts related to writing studies, Adler-Kassner and Wardle and their collaborators identified 37 threshold concepts, some of which may be more applicable to the study and activity of certain genres of writing than others. Granted, this work is not intended for broad implementation the way the Framework is, but both documents are of a similar spirit. 52

As stated earlier, students often enter the information literacy classroom unable to recognize that, while the skills and knowledge they have developed are valuable in some research contexts, they may be less so in others. For information literacy instructors, this has been a significant barrier, one that the Standards provided no meaningful way to overcome. The metaconcept that has been established here gives us a lens through which to understand research as not just an activity but also a subject of study. The Framework provides a path to pass on this knowledge to students by introducing them to the importance of context to the research process. The next section describes how a common model for composition instruction could be adapted for this purpose.

A Suggested Model for Practical Application

In Standards -based information literacy instruction, students are introduced to the conventions of academic research at the same time that they are expected to apply those conventions. They are expected to do this correctly without ever having seen or studied an example of such research, except perhaps one provided by their instructor for informational purposes. Badke criticizes this approach, colorfully stating, “teaching application without teaching method and philosophy is akin to showing someone how to steer and use the brakes on a car without teaching overall driving technique and the rules of the road.” 53

In writing studies, there is a similar expectation that, as Sommers and Saltz put it, students will “become master builders while they are still apprentices.” 54 However, composition instruction does not generally begin and end with application the way information literacy instruction does. Instead, students first study a selected example of a genre of writing to learn about the conventions of that genre and then attempt to apply those conventions in their own work. Information literacy instruction could benefit from emulating this structure.

Rather than organizing an information literacy course around units based on skills, sources, or tools, the course could be organized instead around different research contexts. More work may need to be done to determine what exactly those contexts can or should be or whether the conventions, goals, and motivations of those contexts can be said to represent “genres” as the term is understood by researchers of genre theory. 55 However, a general information literacy course could conceivably be organized around units on academic research, personal research, professional research, creative research, scientific research, and more.

In this approach, research skills like those described by the Standards would still be valuable but would only be taught after students first had the opportunity to study an example piece of research. Similar to the work of some professionals who study research, students could closely examine the types of sources used and think about the roles those sources play in the author’s research. They might also study the way the author gives credit to those sources, perhaps noticing that, in some research contexts, credit is given through formal citation while in others it is done through contextual links, quotes from interview subjects, or some other way. By doing this, students would learn how the conventions of research change from context to context. They may begin to develop a more realistic view of how much more there is to learn beyond the skills they already have and why it is worth learning.

As an illustration of how a unit in a course designed like this would work, consider that in a composition course students might first be given Letter from a Birmingham Jail by Martin Luther King Jr. as an example of persuasive writing. They would study this piece before trying to emulate King’s rhetorical moves in their own work.

In a unit on academic research in an information literacy course, students might first be given an example research essay or scholarly article. Rather than studying the writing, they would look at the evidence of research in the source. They might be asked to notice how the author uses citations or footnotes and includes a list of sources at the end. Attention might be drawn to the nature of the sources the author used, and critical thought might be given to why he or she made those choices. A student could also be asked to comment on how each source was used in the example piece: to add new information, to present and answer a contradicting view, to pull a quote, and so on.

The same could be done with units on other types of research. In a different unit, a personal blog post could be used as an example of personal research in which the evidence of research might appear as contextual links rather than formal citations. Or a news article could be studied as an example of journalistic or professional research in which quotes from sources with firsthand knowledge of an event are privileged over other types of sources. Even King’s Letter could be used as an example of research. In this piece, King borrows ideas from and makes reference to Socrates and the Bible to support his ideas. He also relies on the authority granted to him by his own personal experience with the issues he is discussing. 56

After studying the conventions of a genre of research through an example piece, students could then be taught the skills needed to complete the type of research each product represents. As a culminating project, students could be required to create a research product of their own that follows the conventions they learned about and then reflect on the ways that they used or challenged those conventions in their own work.

What is described above would be most appropriate for a general information literacy course taught at the undergraduate level. Instructors who teach more advanced or discipline-based information literacy could adapt this approach to suit their students’ needs and interests. For example, such instruction could focus more closely on the evaluation of research as it is most often represented in a field of study or profession. Students could be taught to see flaws in an author’s methodology, reasoning, or use of sources. They might also benefit from reviewing studies of information behavior of relevant populations to gain an understanding of how these populations interact with and create information in various settings. Instructors could invite students to think critically about the research practices in their fields and reflect on areas of potential improvement.

Caveats and Potential Concerns

It is necessary at this point to acknowledge that the common model for teaching composition described earlier is not without its critics in that field. Connors, for example, argues that using genres and modes to teach writing is more of a convenience to the instructor than a reflection of how writing actually works. 57 Hillocks makes the case that using genre and form to teach composition neglects the importance of inquiry and teaching students how to work with content. 58

In implementing a similar model for information literacy instruction, information literacy instructors may also have concerns. Foremost among these may be a reluctance to teach research outside the discipline-agnostic academic context of past Standards -based instruction. To do so, it has been argued in the past, would be to tread on the toes of disciplinary faculty who are the rightfully recognized experts on research in their fields of study and also perhaps to stray outside our professional strengths. 59 In response to this, it must be acknowledged that disciplinary faculty have been valuable partners in teaching information literacy in the past and could continue to be so in this new approach. As far as professional strengths, the Standards may have been limited to library-based academic research but the study of research in the LIS field is not, showing that contexts outside academia are, in fact, within our professional domain. Even if they were not, librarians tend to portray themselves as research experts as a way of communicating their value to their institutions. Taking advantage of the ways in which researchers in our own field have cultivated an understanding of how research works in a variety of contexts can only enhance our ability to label ourselves this way.

Another possible area of concern might be one anticipated by Townsend, Brunetti, and Hofer who acknowledge that threshold concepts like the ones found in the Framework tend to privilege certain ways of thinking. 60 Information literacy instructors may feel that the study of research is for professionals only and that teaching it to students would set up an expectation that, to be successful researchers, they need to become junior librarians or junior professors. However, it is worth noting that the goal of composition instruction, which involves both the study and practice of writing, is to teach students to be competent writers with an appreciation for rhetorical context. They are introduced to expert ways of thinking as a way of expanding their worldview but are not expected to become published (or even publishable) authors as a result of what they learn.

Finally, there may be some question of whether teaching students the conventions associated with different research contexts and then expecting them to follow those conventions stifles creativity by inviting conformity to existing systems. In answer to this, it could be argued that using the conventions of research as a teaching tool opens the door to conversations about why those conventions exist in the first place and in what ways they uphold what Beilin refers to as the “knowledge regime.” 61 Teaching students to think critically about the research that goes into creating a particular research product would enable them to more clearly see how the recontextualization process that is part of all research is subject to the inherent biases and worldviews of the author. 62 Even more important, as observed by Simmons, when students learn about generic conventions, they may learn to see themselves as having “the potential to effect changes in the conventions instead of simply learning to conform to the established patterns.” 63 In other words, learning “the rules” is also the first step in learning how to break those rules and challenge the systems that created them in meaningful and interesting ways.

Current models of information literacy instruction that treat research as nothing more than a basic skill do not serve students well. They also do not serve information literacy well. Research is not a basic skill that can be mastered for a lifetime in the space of a single instruction session. It is an activity that relies heavily on rhetorical context. It is also a subject of study with areas of inquiry in which context is often a large consideration. To paraphrase Wardle and Adler-Kassner, 64 a successful researcher is someone who cultivates an understanding of the expectations associated with research in a given context and then meaningfully engages with those expectations. Such a researcher is both a consumer and a creator of information.

The metaconcept introduced in this article, that research is both an activity and a subject of study, is an attempt to name something that has been present in LIS literature all along but for which there has been no room in information literacy instruction in the past. Future work to identify the ways in which this metaconcept has manifested itself in the literature in our field will be valuable in helping us to articulate the value of our work in a new way. In the meantime, it could serve as a useful frame for transforming information literacy instruction and enhancing the reputation of information literacy as something more than a basic skill.

1. Valeria E. Molteni and Emily K. Chan, “Student Confidence/Overconfidence in the Research Process,” Journal of Academic Librarianship 41, no. 1 (2015): 2–8.

2. Nancy Sommers and Laura Saltz, “The Novice as Expert: Writing the Freshman Year,” College Composition and Communication 56, no. 1 (2004): 124–49.

3. Elizabeth Wardle and Linda Adler-Kassner, “Metaconcept: Writing Is an Activity and a Subject of Study,” in Naming What We Know: Threshold Concepts of Writing Studies , eds. Linda Adler-Kassner and Elizabeth Wardle (Boulder: University Press of Colorado, 2015), 15–16.

4. Office for Human Research Protection, “Basic HHS Policy for Protection of Human Research Subjects” (2009), available online at https://www.hhs.gov/ohrp/regulations-and-policy/regulations/45-cfr-46/index.html [accessed 23 January 2018].

5. ACRL Information Literacy Competency Standards for Higher Education , “Information Literacy Defined” (2000), available online at www.ala.org/acrl/standards/informationliteracycompetency [accessed 23 January 2018].

6. ACRL Framework for Information Literacy for Higher Education , “Introduction” (2015), available online at www.ala.org/acrl/standards/ilframework [accessed 23 January 2018].

7. T.D. Wilson, “Models in Information Behaviour Research,” Journal of Documentation 55, no. 3 (1999): 251.

8. Judith M. Nixon, “Core Journals in Library and Information Science: Developing a Methodology for Ranking LIS Journals,” College & Research Libraries 75, no. 1 (2014): 66–90.

9. Examples include: Stephen E. Atkins, “Subject Trends in Library and Information Science Research, 1975–1984,” Library Trends 36, no. 4 (Spring 1988): 633–58; Lois Buttlar, “Analyzing the Library Periodical Literature: Content and Authorship,” College & Research Libraries 52, no. 1 (Jan. 1991): 38–53; Gloria S. Cline, ” College & Research Libraries : Its First Forty Years,” College & Research Libraries 43, no. 3 (1982): 208–32; Gregory A. Crawford, ”The Research Literature of Academic Librarianship: A Comparison of College & Research Libraries and Journal of Academic Librarianship ,” College & Research Libraries 60, no. 3 (1999): 224–30; Amy VanScoy and Cady Fontana, “How Reference and Information Services is Studied: Research Approaches and Methods,” Library & Information Science Research 38, no. 2 (2016): 94–100.

10. Otto Tuomaala, Kalervo Jarvelin, and Pertti Vakkari, “Evolution of Library and Information Science, 1965–2005: Content Analysis of Journal Articles,” Journal of the Association for Information Science & Technology 65, no. 7 (2014): 1446–62.

11. Steven Buchanan and Lauren Tuckerman, “The Information Behaviours of Disadvantaged and Disengaged Adolescents,” Journal of Documentation 72, no. 3 (2016): 527–48; Jacob Dankasa, “Mapping the Everyday Life Information Needs of Catholic Clergy: Savolainen’s ELIS Model Revisited,” Journal of Documentation 72, no. 3 (2016): 549–68; Maja Krtalic, Sanjica Faletar Tanackovic, and Damir Hasenay, “Linguists as Newspaper Users: Perceptions and Experiences,” Library and Information Science Research 38, no. 2 (2016): 108–16; Grace Msoffe and Patrick Ngulube, “Farmers’ Access to Poultry Management Information in Selected Areas of Tanzania,” Library and Information Science Research 38, no. 3 (2016): 82–90.

12. Examples include: Nancy Falciani-White, “Understanding the ‘Complexity of Experience’: Modeling Faculty Research Practices,” Journal of Academic Librarianship 42, no. 2 (2016): 118–26; Christopher V. Hollister, “An Exploratory Study on Post-tenure Research Productivity Among Academic Librarians,” Journal of Academic Librarianship 42, no. 4 (2016): 368–81; Sloan Komissarov and James Murray, “Factors That Influence Undergraduate Information-seeking Behavior and Opportunities for Student Success,” Journal of Academic Librarianship 42, no. 4 (2016): 423–49; Carol Sabbar and Iris Xie, “Language in the Information-Seeking Context: A Study of U.S. Scholars Using Non-English Sources,” Journal of Documentation 72, no. 1 (2016): 103–26.

13. Examples include: Lisa M. Given et al., “Watching Young Children ‘Play’ with Information Technology: Everyday Life Information Seeking in the Home,” Library and Information Science Research 38, no. 4 (2016): 344–52; Helena Känsäkoski and Maija-Leena Huotari, “Applying the Theory of Information Worlds Within a Health Care Practise in Finland,” Journal of Documentation 72, no. 2 (2016): 321–41; Reijo Savolainen, “Approaches to Socio-Cultural Barriers to Information Seeking,” Library and Information Science Research 38, no. 1 (2016): 52–59.

14. Examples include: Elham Sayyad Abdi, Helen Partridge, and Christine Bruce, “Web Designers and Developers’ Experience of Information Literacy: A Phenomenographic Study,” Library and Information Science Research 38, no. 4 (2016): 353–59; Rebecca Lea French and Kirsty Williamson, “The Information Practices of Welfare Workers: Conceptualizing and Modelling Information Bricolage,” Journal of Documentation 72, no. 4 (2016): 737–54; Ayse Göker et al., “Expeditions Through Image Jungles: The Commercial Use of Image Libraries in an Online Environment,” Journal of Documentation 72, no. 1 (2016): 5–23.

15. Examples related to each theme mentioned include: Nicolas Robinson-Garcia, Evaristo Jimenez-Contreras, and Daniel Torres-Salinas, “Analyzing Data Practices Using the Data Citation Index,” Journal of the Association for Information Science & Technology 67, no. 12 (2016): 2964–75; Angela Dresselhaus, “Literature of Acquisitions in Review, 2012–2013,” Library Resources & Technical Services 60, no. 3 (2016): 169–81; and Dian Walster, Deborah H. Charbonneau, and Kafi Kumasi, “Finding and Reading Reports of Research: How Academic Librarians Can Help Students Be More Successful,” Journal of Academic Librarianship 42, no. 6 (2016): 732–38.

16. Examples include: Cheryl D. Bain et al., “Using WorldShare Collection Evaluation to Analyze Physical Science and Engineering Monograph Holdings by Discipline,” Collection Management 41, no. 3 (2016): 133–51; Michael Hughes, “A Long-Term Study of Collection Use Based on Detailed Library of Congress Classification, a Statistical Tool for Collection Management Decisions,” Collection Management 41, no. 3 (2016): 152–67; Blanca Rodriguez-Bravo and Francisco Rodriguez-Sedano, “Trends in Library Collection Circulation in Spanish Universities,” Library Resources & Technical Services 60, no. 4 (2016): 248–58.

17. Examples include: Kelsey Renee Brett, Ashley Lierman, and Cherie Turner, “Lessons Learned: A Primo Usability Study,” Information Technology and Libraries 35, no. 1 (2016): 7–25; Reese Hoi Yin Fung, Dickson K.W. Chiu, Eddie H.T. Ko, Kevin K.W. Ho, and Patrick Lo, “Heuristic Usability Evaluation of University of Hong Kong Libraries’ Mobile Website,” Journal of Academic Librarianship 42, no. 5 (2016): 581–94; Joanne Oud, “Accessibility of Vendor-Created Database Tutorials for People with Disabilities,” Information Technology and Libraries 35, no. 4 (2016): 7–18; Kyunghye Yoon et al., “An Exploratory Study of Library Website Accessibility for Visually Impaired Users,” Library & Information Science Research 38, no. 3 (2016): 250–58.

18. Examples include: Çağrı Imamoğlu and Meltem Ö. Gürel, “‘Good Fences Make Good Neighbors’: Territorial Dividers Increase User Satisfaction and Efficiency in Library Study Spaces,” Journal of Academic Librarianship 42, no. 1 (2016): 65–73; Vera Lux, Robert J. Snyder, and Colleen Boff, “Why Users Come to the Library: A Case Study of Library and Non-Library Units,” Journal of Academic Librarianship 42, no. 2 (2016): 109–17; Silas M. Oliveira, “Space Preferences at James White Library: What Students Really Want,” Journal of Academic Librarianship 42, no. 4 (2016): 355–67.

19. Examples include: Edward Kai Fung Dang, Robert W.P. Luk, and James Allan, “A Context-Dependent Relevance Model,” Journal of the Association for Information Science & Technology 67, no. 3 (2016): 582–93; Bo Xu, Hongfei Lin, and Yuan Lin, “Assessment of Learning to Rank Methods for Query Expansion,” Journal of the Association for Information Science & Technology 67, no. 6 (2016): 1345–57.

20. Gloria J. Leckie, (1996). “Desperately Seeking Citations: Uncovering Faculty Assumptions About the Undergraduate Research Process,” Journal of Academic Librarianship 22, no. 3 (1996): 201–08.

21. Claire Warwick et al., “Cognitive Economy and Satisficing in Information Seeking: A Longitudinal Study of Undergraduate Information Behavior,” Journal of the American Society for Information Science & Technology 60, no. 12 (2009): 2402–15.

22. James P. Purdy, “Why First-Year College Students Select Online Research Resources as Their Favorite,” First Monday 17, no. 9 (2012).

23. Kyung-Sun Kim and Sei-Ching Joanna Sin, “Selecting Quality Sources: Bridging the Gap Between the Perception and Use of Information Sources,” Journal of Information Science 37, no. 2 (2011): 178–88.

24. Allison J. Head, Michele Van Hoeck, Jordan Eschler, and Sean Fullerton, “What Information Competencies Matter in Today’s Workplace?” Library and Information Research 37, no. 114 (2013): 75–104.

25. Barbara Fister, “Teaching the Rhetorical Dimensions of Research,” Research Strategies 11, no. 4 (1993): 211–19.

26. Jeanne R. Davidson and Carole Anne Crateau. “Intersections: Teaching Research Through a Rhetorical Lens,” Research Strategies 16, no. 4 (1998): 245–57.

27. Michelle Holschuh Simmons, “Librarians as Disciplinary Discourse Mediators: Using Genre Theory to Move toward Critical Information Literacy,” portal: Libraries and the Academy 5, no. 3 (2005): 297–311.

28. Benjamin R. Harris, “Communities as Necessity in Information Literacy Development: Challenging the Standards,” Journal of Academic Librarianship 34, no. 3 (2008): 250.

29. Allison Faix, “Assisting Students to Identify Sources: An Investigation,” Library Review 53, no. 8/9 (2014): 624–36.

30. Doug Brent, “Crossing Boundaries: Co-Op Students Relearning to Write,” College Composition and Communication 63, no. 4 (2012): 558–92; Sarah North, “Different Values, Different Skills? A Comparison of Essay Writing by Students from Arts and Science Backgrounds,” Studies in Higher Education 30, no. 5 (2005): 517–33.

31. Jens B. Asendorpf et al., “Recommendations for Increasing Replicability in Psychology,” European Journal of Personality 27, no. 2 (2013): 108–19.

32. Examples include: Shane W. Bench et al., “Does Expertise Matter in Replication? An Examination of the Reproducibility Project: Psychology,” Journal of Experimental Social Psychology 68 (2017): 181–84; and Alexander Etz and Joachim Vandekerckhove, “A Bayesian Perspective on the Reproducibility Project: Psychology,” Plos One 11, no. 2 (2016): 1–12.

33. Wolfgang Stroebe, “Are Most Published Social Psychological Findings False?” Journal of Experimental Social Psychology 66 (2016): 134–44.

34. Examples include: Mark J. Brandt et al., “The Replication Recipe: What Makes for a Convincing Replication?” Journal of Experimental Social Psychology 50 (2014): 217–24; and Sean Grant, Lukasz Cybulski, and Evan Mayo-Wilson, “Improving Transparency and Reproducibility through Registration: The Status of Intervention Trials Published in Clinical Psychology Journals,” Journal of Consulting and Clinical Psychology 84, no. 9 (2016): 753–67.

35. Uri Simonsohn, “Small Telescopes: Detectability and the Evaluation of Replication Results,” Psychological Science 26, no. 5 (2015): 559–69.

36. Timothy M. Errington et al., “Science Forum: An Open Investigation of the Reproducibility of Cancer Biology Research,” eLife 3 (2014).

37. Shirley J. Behrens, “A Conceptual Analysis and Historical Overview of Information Literacy,” College & Research Libraries 55, no. 4 (1994): 309–22; Frances L. Hopkins, “A Century of Bibliographyic Instruction: The Historical Claim to Professional and Academic Legitimacy,” College & Research Libraries 43, no. 3 (1982): 192–98; Mary F. Salony, “The History of Bibliographic Instruction: Changing Trends From Books to the Electronic World,” Reference Librarian 24, no. 51 (1995): 31–51.

38. Emily Drabinski, “Toward a Kairos of Library Instruction,” Journal of Academic Librarianship 40, no. 5 (2014): 480–85; Heidi L.M. Jacobs, “Information Literacy and Reflective Pedagogical Praxis,” Journal of Academic Librarianship 34, no. 3 (2008): 256–62.

39. ACRL Standards , “Information Literacy and Assessment.”

40. Notable examples of such thinking include: James Elmborg, “Critical Information Literacy: Implications for Instructional Practice,” Journal of Academic Librarianship 32, no. 2 (2006): 192–99; Edward K. Owusu-Ansah, “Information Literacy and the Academic Library: A Critical Look at a Concept and the Controversies Surrounding It,” Journal of Academic Librarianship 29, no. 4 (2003): 219–30; Troy A. Swanson, “Applying a Critical Pedagogical Perspective to Information Literacy Standards,” Community & Junior College Libraries 12, no. 4 (2004): 65–78: Eamon Tewell, “A Decade of Critical Information Literacy: A Review of the Literature,” Communications in Information Literacy 9, no. 1 (2015): 24–43.

41. ACRL Standards , “Information Literacy Defined”; ACRL Standards , “Information Literacy and Higher Education.”

42. Examples include: Brent, “Crossing Boundaries”; Jason Eyre, “Context and Learning: The Value and Limits of Library-Based Information Literacy Teaching,” Health Information and Libraries Journal 29, no. 4 (2012): 344–48; and Kaye Towlson and Nathan Rush, “Carving the Information Literacy Niche Within Graduate Employability ,” New Review of Academic Librarianship 19, no. 3 (2013): 300–15.

43. Amy E. Mark, “Privileging Peer Review: Implications for Undergraduates ,” Communications in Information Literacy 5, no. 1 (2011): 4–8.

44. Association of American Colleges & Universities, “Information Literacy VALUE Rubric” (2010), available online at https://www.aacu.org/value/rubrics/information-literacy [accessed 23 January 2018]; Middle States Association of Colleges and Schools Commission on Higher Education, Developing Research & Communication Skills: Guidelines for Information Literacy Instruction (Philadelphia: Middle States Commission on Higher Education, 2003).

45. Paul L. Hrycaj, “An Analysis of Online Syllabi for Credit-Bearing Library Skills Courses,” College & Research Libraries 67, no. 6 (2006): 525–35; Rachael E. Elrod, Elise D. Wallace, and Cecilia B. Sirigos, “Teaching Information Literacy: A Review of 100 Syllabi,” Southeastern Librarian 60, no. 3 (2012): 8–15.

46. Amy R. Hofer, Lori Townsend, and Korey Brunetti, “Troublesome Concepts and Information Literacy: Investigating Threshold Concepts for IL Instruction,” portal: Libraries and the Academy 12, no. 4 (2012): 387–405.

47. Shelley Gullikson, “Faculty Perceptions of ACRL’s Information Literacy Competency Standards for Higher Education,” Journal of Academic Librarianship 32, no. 6 (2006): 583–92.

48. Rolf Norgaard, “Writing Information Literacy: Contributions to a Concept,” Reference & User Services Quarterly 43, no. 2 (2003): 126.

49. ACRL Framework , “Introduction.”

50. Nancy M. Foasberg, “From Standards to Frameworks for IL: How the ACRL Framework Addresses Critiques of the Standards ,” portal: Libraries and the Academy 15, no. 4 (2015): 708.

51. ACRL Framework , “Introduction.”

52. Elizabeth Wardle and Linda Adler-Kassner, “Naming What We Know: The Project of This Book,” in Naming What We Know: Threshold Concepts of Writing Studies, eds. Linda Adler-Kassner and Elizabeth Wardle (Boulder: University Press of Colorado, 2015), 8.

53. William Badke, “A Rationale for Information Literacy as a Credit-Bearing Discipline ,” Journal of Information Literacy 2, no. 1 (2008).

54. Sommers and Saltz, “The Novice as Expert,” 132.

55. Amy J. Devitt, Writing Genres (Carbondale: Southern Illinois University Press, 2004).

56. Martin Luther King, Jr., Letter from a Birmingham Jail , available online at https://kinginstitute.stanford.edu/king-papers/documents/letter-birmingham-jail [accessed 23 January 2018].

57. Robert J. Connors, “The Rise and Fall of the Modes of Discourse,” College Composition and Communication 32, no. 4 (1981): 444–55.

58. George Hillocks, Jr., “The Focus on Form vs. Content in Teaching Writing,” Research in the Teaching of English 40, no. 2 (2005): 238–48.

59. Richard Feinberg and Christine King, “Short-Term Library Skill Competencies: Arguing for the Achievable,” College & Research Libraries 49, no. 1 (1988): 24–28.

60. Lori Townsend, Korey Brunetti, and Amy R. Hofer, “Threshold Concepts and Information Literacy,” portal: Libraries and the Academy 11, no. 3 (2011): 853–69.

61. Ian Beilin, “Beyond the Threshold: Conformity, Resistance, and the ACRL Information Literacy Framework for Higher Education,” In the Library with the Lead Pipe (Feb. 25, 2015), available online at www.inthelibrarywiththeleadpipe.org/2015/beyond-the-threshold-conformity-resistance-and-the-aclr-information-literacy-framework-for-higher-education/ [accessed 26 October 2018].

62. Christine Pawley, “Information Literacy: A Contradictory Coupling,” Library Quarterly 73, no. 4 (2003): 422–52.

63. Simmons, “Librarians as Disciplinary Discourse Mediators,” 302.

64. Wardle and Adler-Kassner, “Metaconcept,” 16.

* Allison Hosier is Information Literacy Librarian in the University Libraries at the University at Albany, State University of New York; email: [email protected] . ©2019 Allison Hosier, Attribution-NonCommercial ( http://creativecommons.org/licenses/by-nc/4.0/ ) CC BY-NC.

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Research Object Crate

RO-Crate has been developed as a schema.org-based JSON lightweight approach to the next generation Research Object serialization.

2020-10-30: The specification RO-Crate 1.1 has been released. Join the community to help further develop RO-Crate!

Workshop on Research Objects (RO2019)

The RO2019 workshop was at IEEE eScience Conference 2019 in San Diego, US. This successful workshop followed the initial RO2018 . Proceedings of accepted papers and talks are available, along with links to slides and posters .

Researchobject.org aims to map the landscape of initiatives and activity in the development of Research Objects , an emerging approach to the publication, and exchange of scholarly information on the Web. Research Objects aim to improve reuse and reproducibility by:

• Supporting the publication of more than just PDFs , making data , code , and other resources first class citizens of scholarship
• Recognizing that there is often a need to publish collections of these resources together as one shareable , cite-able resource.
• Enriching these resources and collections with any and all additional information required to make research reusable , and reproducible !

Research objects are not just data, not just collections, but any digital resource that aims to go beyond the PDF for scholarly publishing!

Going beyond the PDF

Science advances on a foundation of trusted discoveries. Reproducing an experiment is one important approach that scientists use to gain confidence in their conclusions. Marcia McNutt, Editor-in-Chief of Science

The reuse and reproduction of scientific experiments as they are described in publications can be hard. Often it requires additional information, data, tooling or support beyond that provided in the text of a traditional publication.

As part of one research investigation you might for example have:

• Slides hosted on slideshare,
• Code in a github repository,
• Data in figshare,
• Data in ArrayExpress.

A growing number of activities are developing new mechanisms, or repurposing existing mechanisms in order to describe and associate resources like this together, in a machine-readable manner, so that they can be more easily shared, and exchanged.

The goal of research objects is to improve the potential for understanding and reuse of research by making sure that the information that is needed to make a published resource useful is associated with it, and shared as a whole.

There are a growing number of, individuals, groups, and initiatives – all trying to improve the state of scholarly publication. These range from domain specific to general, and from the practical and immediately actionable, to the more visionary and experimental.

What is emerging from these activities is a common set of goals and principles – features that are required required to support research that is Findable , Accessible , Interoperable , and Reusable (FAIR).

To understand more about the principles , goals of the Research Object approach, head over to the Overview page.

To discover the range of on going activities, and mechanisms that can be used to build research objects, check out the RO Initiatives & Resources page.

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RO-Crate 1.0 specification released

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2019-09-24: Workshop on Research Objects (RO2019)

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2018-10-03 Being FAIR: Enabling Reproducible Data Science

Posted on 15 October 2018

2018-10-29 Workshop on Research Objects

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2017-12-05 FAIRy Stories for Christmas

Posted on 5 December 2017

2017-11-15 Managing Digital Research Objects in an Expanding Science Ecosystem

Posted on 1 December 2017

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2017-11-27 BioCompute Objects

Posted on 9 November 2017

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Posted on 27 October 2017

2017-10-21 Keynote at SemSci ISWC 2017

Posted on 21 October 2017

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2017-09-27 eLife Reproducible Portable Publications

Posted on 27 September 2017

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2017-07-22 Common Workflow Language Viewer

Posted on 22 July 2017

2017-07-17 Being Reproducible (SSBSS Summer School)

Posted on 17 July 2017

2016-05-18 Make Research Reproducible Again

Posted on 18 May 2016

2016-01-28 Reproducibility Using Semantics

Posted on 29 January 2016

2016-01-28 ROHub

Posted on 28 January 2016

2016-01-28 Research Objects, FAIRDOM and SEEK4Science

2016-01-28 aspects of reproducibility in earth science, bagit for transferring and archiving research objects.

Posted on 17 July 2015

• specification

Research Objects at BOSC

Research objects biocaddie webinar, why publish and be so damned hard to find.

Posted on 23 March 2015

JISC Digifest Keynote

Posted on 11 March 2015

Combining Docker & R for Reproducible Research

Posted on 10 March 2015

RO+ISA+Nanopublication: What can you do when you put all three of them together?

Posted on 6 August 2014

Example of Encoding an RO using RDF-a

Posted on 28 February 2014

Our Workshop on "What Bioinformaticians need to know about digital publishing beyond the PDF2" has been accepted for ISMB2014

Posted on 14 January 2014

The Launch of Research Object Creator Tool (Give it a try!)

Posted on 10 January 2014

Quantifying Reproducibility in Computational Biology: The Case of the Tuberculosis Drugome

Posted on 17 November 2013

10th International Conference on Preservation of Digital Objects

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From Preserving Data to Preserving Research:Curation of Process and Context

Posted on 21 May 2013

The Now and Future of Data Publishing, a symposium, 22 May 2013, Oxford, UK

Posted on 16 May 2013

Posted on 14 May 2013

Wf4Ever in ISMB/ECCB 2013

10th eswc 2013 semantics and big data.

Posted on 4 May 2013

Launch of W3C Research Object for Scholarly Communication Community Group

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Study explains why the brain can robustly recognize images, even without color

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Even though the human visual system has sophisticated machinery for processing color, the brain has no problem recognizing objects in black-and-white images. A new study from MIT offers a possible explanation for how the brain comes to be so adept at identifying both color and color-degraded images.

Using experimental data and computational modeling, the researchers found evidence suggesting the roots of this ability may lie in development. Early in life, when newborns receive strongly limited color information, the brain is forced to learn to distinguish objects based on their luminance, or intensity of light they emit, rather than their color. Later in life, when the retina and cortex are better equipped to process colors, the brain incorporates color information as well but also maintains its previously acquired ability to recognize images without critical reliance on color cues.

The findings are consistent with previous work showing that initially degraded visual and auditory input can actually be beneficial to the early development of perceptual systems.

“This general idea, that there is something important about the initial limitations that we have in our perceptual system, transcends color vision and visual acuity. Some of the work that our lab has done in the context of audition also suggests that there’s something important about placing limits on the richness of information that the neonatal system is initially exposed to,” says Pawan Sinha, a professor of brain and cognitive sciences at MIT and the senior author of the study.

The findings also help to explain why children who are born blind but have their vision restored later in life, through the removal of congenital cataracts, have much more difficulty identifying objects presented in black and white. Those children, who receive rich color input as soon as their sight is restored, may develop an overreliance on color that makes them much less resilient to changes or removal of color information.

MIT postdocs Marin Vogelsang and Lukas Vogelsang, and Project Prakash research scientist Priti Gupta, are the lead authors of the study, which appears today in Science . Sidney Diamond, a retired neurologist who is now an MIT research affiliate, and additional members of the Project Prakash team are also authors of the paper.

Seeing in black and white

The researchers’ exploration of how early experience with color affects later object recognition grew out of a simple observation from a study of children who had their sight restored after being born with congenital cataracts. In 2005, Sinha launched Project Prakash (the Sanskrit word for “light”), an effort in India to identify and treat children with reversible forms of vision loss.

Many of those children suffer from blindness due to dense bilateral cataracts. This condition often goes untreated in India, which has the world’s largest population of blind children, estimated between 200,000 and 700,000.

Children who receive treatment through Project Prakash may also participate in studies of their visual development, many of which have helped scientists learn more about how the brain's organization changes following restoration of sight, how the brain estimates brightness, and other phenomena related to vision.

In this study, Sinha and his colleagues gave children a simple test of object recognition, presenting both color and black-and-white images. For children born with normal sight, converting color images to grayscale had no effect at all on their ability to recognize the depicted object. However, when children who underwent cataract removal were presented with black-and-white images, their performance dropped significantly.

This led the researchers to hypothesize that the nature of visual inputs children are exposed to early in life may play a crucial role in shaping resilience to color changes and the ability to identify objects presented in black-and-white images. In normally sighted newborns, retinal cone cells are not well-developed at birth, resulting in babies having poor visual acuity and poor color vision. Over the first years of life, their vision improves markedly as the cone system develops.

Because the immature visual system receives significantly reduced color information, the researchers hypothesized that during this time, the baby brain is forced to gain proficiency at recognizing images with reduced color cues. Additionally, they proposed, children who are born with cataracts and have them removed later may learn to rely too much on color cues when identifying objects, because, as they experimentally demonstrated in the paper, with mature retinas, they commence their post-operative journeys with good color vision.

To rigorously test that hypothesis, the researchers used a standard convolutional neural network, AlexNet, as a computational model of vision. They trained the network to recognize objects, giving it different types of input during training. As part of one training regimen, they initially showed the model grayscale images only, then introduced color images later on. This roughly mimics the developmental progression of chromatic enrichment as babies’ eyesight matures over the first years of life.

Another training regimen comprised only color images. This approximates the experience of the Project Prakash children, because they can process full color information as soon as their cataracts are removed.

The researchers found that the developmentally inspired model could accurately recognize objects in either type of image and was also resilient to other color manipulations. However, the Prakash-proxy model trained only on color images did not show good generalization to grayscale or hue-manipulated images.

“What happens is that this Prakash-like model is very good with colored images, but it’s very poor with anything else. When not starting out with initially color-degraded training, these models just don’t generalize, perhaps because of their over-reliance on specific color cues,” Lukas Vogelsang says.

The robust generalization of the developmentally inspired model is not merely a consequence of it having been trained on both color and grayscale images; the temporal ordering of these images makes a big difference. Another object-recognition model that was trained on color images first, followed by grayscale images, did not do as well at identifying black-and-white objects.

“It’s not just the steps of the developmental choreography that are important, but also the order in which they are played out,” Sinha says.

The advantages of limited sensory input

By analyzing the internal organization of the models, the researchers found that those that begin with grayscale inputs learn to rely on luminance to identify objects. Once they begin receiving color input, they don’t change their approach very much, since they’ve already learned a strategy that works well. Models that began with color images did shift their approach once grayscale images were introduced, but could not shift enough to make them as accurate as the models that were given grayscale images first.

A similar phenomenon may occur in the human brain, which has more plasticity early in life, and can easily learn to identify objects based on their luminance alone. Early in life, the paucity of color information may in fact be beneficial to the developing brain, as it learns to identify objects based on sparse information.

“As a newborn, the normally sighted child is deprived, in a certain sense, of color vision. And that turns out to be an advantage,” Diamond says.

Researchers in Sinha’s lab have observed that limitations in early sensory input can also benefit other aspects of vision, as well as the auditory system. In 2022, they used computational models to show that early exposure to only low-frequency sounds, similar to those that babies hear in the womb, improves performance on auditory tasks that require analyzing sounds over a longer period of time, such as recognizing emotions. They now plan to explore whether this phenomenon extends to other aspects of development, such as language acquisition.

The research was funded by the National Eye Institute of NIH and the Intelligence Advanced Research Projects Activity.

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Stereolithographic Rapid Prototyping of Clear, Foldable, Non-Refractive Intraocular Lens Designs: A Proof-of-Concept Study

Affiliations.

• 1 School of Pharmacy, University of East Anglia, Norwich, UK.
• 2 School of Biological Sciences, University of East Anglia, Norwich, UK.
• PMID: 38762982
• DOI: 10.1080/02713683.2024.2344164

Purpose: A cataract is a cloudy area in the crystalline lens. Cataracts are the leading cause of blindness and the second cause of severe vision impairment worldwide. During cataract surgery, the clouded lens is extracted and replaced with an artificial intraocular lens, which restores the optical power. The fabrication of intraocular lenses using existing molding and lathing techniques is a complex and time-consuming process that limits the development of novel materials and designs. To overcome these limitations, we have developed a stereolithography-based process for producing models of clear lens designs without refractive function, serving as a proof of concept. This process has the potential to contribute toward new lens development, allowing for unlimited design iterations and an expanded range of materials for scientists to explore.

Methods: Lens-like 3D objects without refractive function were fabricated by using stereolithography. A photopolymerizable resin containing 2-phenoxyethyl acrylate, poly (ethylene glycol) dimethacrylate, and a suitable photoinitiator was developed for the production of lens-like 3D object prototypes. The morphology of the printed devices was characterized by scanning electron microscopy. The transparency and thermal properties were analyzed using spectrophotometry and differential scanning calorimetry, respectively. The biocompatibility of the devices was investigated in a cultured human lens cell line (FHL-124), using a standard lactate dehydrogenase assay, and the lenses were folded and implanted in the human capsular bag model.

Results: One-piece lens-like 3D objects without refractive function and with loop-haptic design were successfully fabricated using Stereolithography (SLA) technique. The resulting 3D objects were transparent, as determined by UV spectroscopy. The lactate dehydrogenase test demonstrated the tolerance of lens cells to the prototyping material, and apparent foldability and shape recovery was observed during direct injection into a human capsular bag model in vitro .

Conclusions: This proof-of-principle study demonstrated the potential and significance of the rapid prototyping process for research and development of lens-like 3D object prototypes, such as intraocular lenses.

Keywords: 3D printing of intraocular lenses; Cataract; intraocular lens; optics; refractive surgery.

UWM's Neeskay research vessel studies the Great Lakes year-round

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And to understand and protect it, scientists need to be out on the water. 

The University of Wisconsin-Milwaukee School of Freshwater Sciences has made its mark on Great Lakes research. It’s the only graduate school of freshwater sciences in the country and one of only three in the world. 

UW-Milwaukee’s main research vessel, the Neeskay, is the only research vessel out on the lakes year-round. 

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But the Neeskay, along with a fleet of small boats, are only just the start. The university has been raising money since 2016 to build the Maggi Sue, which will become the most technologically advanced freshwater research ship in the country. 

The Maggi Sue is expected to open many doors in understanding what’s going on out in the Great Lakes. 

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Customary international law.

• Kathleen Barrett Kathleen Barrett Department of Civic Engagement and Public Service, University of West Georgia
• https://doi.org/10.1093/acrefore/9780190846626.013.531
• Published online: 17 December 2020

Article 38 of the Statute of the International Court of Justice lists “international custom, as evidence of a general practice accepted as law” as the second source of law to be used by the Court. In other words, customary international law (CIL) requires state practice and opinio juris , the belief that the practice is legally required. A basic principle of international law is that sovereign states must consent to be bound by international legal requirements. Therefore, for a norm to become CIL, a widespread group of states must consistently follow the norm and indicate, either explicitly or implicitly, that they consent to the norm. Consistent action is important in two ways: consistent state practice following the norm indicates state consent to be bound by the norm and consistent objection to the norm indicates that the state does not consent to the norm. To avoid being bound by a rule of CIL, a state must persistently object to the rule during and after its formation. Changing CIL requires new state practice and evidence that opinio juris supports the new, not the old, state practice. Debates surrounding state practice include the number of states required to demonstrate “widespread” action, whether the states must be representative of the community of states, and how long consistent practice must occur before CIL is formed. Opinio juris is debated because it is subjective unless there is a specific, official statement that there is a belief that the practice is legally required.

Once a state consents, implicitly or explicitly, to a CIL rule, it cannot withdraw that consent. States that gain independence after a CIL rule is established are bound by that rule if the former government was not a persistent objector. This is problematic, particularly for former colonies that were not able to object during the formation of existing CIL rules because they were not considered “sovereign states.” Scholars supporting this perspective argue that, prior to decolonization, CIL was used to control the colonies and, since their independence, it is used by the colonizers to maintain their power and perpetuate inequality.

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Learning to code and coding to learn: A robotics curriculum integrating tangible programming and road safety education for young children

• Published: 21 May 2024

Cite this article

• Zhenhua Wu   ORCID: orcid.org/0000-0002-0507-6907 1 ,
• Linting Zheng 2 &
• Li’an Huang   ORCID: orcid.org/0000-0002-6454-6366 3  

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Programming has been considered a crucial “object to think with”, which can integrate with various disciplines and facilitate learning in other areas. However, existing research primarily focuses on how children learn to code rather than how coding helps them to learn. To address this gap, a quasi-experimental case study was conducted with 31 kindergarten children, aiming to explore what young children could learn from a 4-week curriculum combining programmable robotics and road safety training. The findings indicate that teaching young children to code not only develops their computational thinking (CT), but also enhances their road safety knowledge and skills. The results contribute to a more comprehensive understanding of early childhood coding education and may inspire the innovation and diversification of coding curricula for young children.

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1.1 Scenarios in Robotics and Programming Curriculum

1.1.1 scenario 1: visiting a friend’s house in the neighborhood.

Description:

Supposing Nini is one of your good friend. Today, you are coming to Nini’s house to play. You need to design a program for the robot going from entrance to Nini’s home according to the map of the neighborhood. Please pay particular attention to the traffic signs on the map.

Scenario map:

1.1.2 Scenario 2: Going from home to kindergarten

Supposing you are going to kindergarten from home by yourself. You need to design a program for the robot going from home to kindergarten according to the provided map. Please pay particular attention to the traffic light and zebra crossings on the map.

1.1.3 Scenario 3: Slowing down

Supposing you are driving a car on the road. Remember you have to slow down when you see such traffic signs as “Pedestrian crossing”, “Children crossing” etc. You need to design a program for the robot going from the parking spot to the park according to the provided map. Please pay particular attention to the traffic signs on the map.

1.1.4 Scenario 4: Finding a parking spot

Supposing you are looking for a parking spot in a public garage. You need to design a program for the robot going from the entrance to the desired parking spot according to the provided map. Please pay particular attention to the traffic signs on the map.

2.1 Traffic Knowledge Assessment Task Scenarios

Scenario 1: Crossing the street 1.

Scenario 2: Crossing the street 2.

Scenario 3: Playing football on the street.

Scenario 4: Driving past a school.

Scenario 5: Turning around.

3.1 Simulated road situation Challenge

The site plan.

Task route and scoring points.

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Wu, Z., Zheng, L. & Huang, L. Learning to code and coding to learn: A robotics curriculum integrating tangible programming and road safety education for young children. Educ Inf Technol (2024). https://doi.org/10.1007/s10639-024-12757-1

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Postdoctoral Scholars (m/f/d)

The Max Planck Institute for the History of Science (MPIWG) is an internationally respected research institute of the Max Planck Society (MPG) with three research departments, several research groups, and a graduate school. At the MPIWG, around three hundred scholars from all over the world investigate the sciences past and present, working together on a collective, collaborative, and trans-disciplinary basis. The MPIWG is renowned worldwide as a hub for reflection on the role of the sciences in politics and society. It is located in southwestern Berlin, close to the campus of the Freie Universität Berlin and other research institutions.

Department “Artifacts, Action, Knowledge” led by Dagmar Schäfer, seeks to appoint  two Postdoctoral Scholars (m/f/d)  – for three years, with employment contract, TVöD-Bund pay scales (E13) – Earliest Start Date: October 1, 2024

Department “Artifacts, Action, Knowledge” studies the history of knowledge and action considering the changing role of artifacts: texts, objects, and spaces.

Our research collectively examines the processes and structures by which people grappled with the materiality of existence. Through the analysis of everyday actions, we interrogate the boundaries and intersections between the inner workings of objects and all domains of life. Together these approaches allow us to pursue inquiries into historical epistemologies of action. For more detailed information, please visit the department website.

Your responsibilities

• Support collaborative research initiatives within the department.
• Conduct an independent research project as part of the " Metals and Minerals: Life from Soil " working group, concentrating on South Asia, Africa, Middle East, or East Asia preceding 1700.
• Contribute to the working group research program in one of two ways, contingent upon experience: through the organization of annual lecture series and events between 2025–2027 or support the organization of a summer school and interdisciplinary training in cooperation with key collaborators
• Engage actively in the research pursuits of the Institute, participate in departmental activities, and deliver presentations on your own research findings.

Your profile

• Hold a Ph.D. degree at the commencement of employment.
• Demonstrate proficiency in a language relevant to the candidate's period of interest, with English being the primary working language of the Institute.

What we offer

• Flexible working hours; the opportunity to work from home as arranged with your superior; the opportunity to work part-time
• Annual year-end bonus; occupational pension (VBL); subsidy for public transportation within Berlin or Germany (“Jobticket”); paid leave on Christmas Eve (December 24) and New Year’s Eve (December 31) in addition to regular annual leave
• Weekly in-house yoga classes; regular information on occupational health management courses offered by our partner health insurance companies
• Access to the wide range of training courses offered by the MPG’s Planck Academy
• Close contact with all research and research-support units with the opportunity for direct, personal dialogue
• An international setting with staff and guests from more than forty countries

The Max Planck Society is an equal opportunity employer that strives to foster an inclusive workplace. As an institute of the MPG, the Max Planck Institute for the History of Science supports a working community for all free from discrimination and harassment. We explicitly encourage applications from qualified individuals who belong to groups that are often underrepresented in the workplace due to age, disability, ethnicity, family status, gender, nationality, race, sex, sexual orientation, socioeconomic background, or religion.

Please follow the links to find out more about the MPIWG’s policies on gender-equality and hiring practices for people with disabilities , as well as Germany’s anti-discrimination laws as outlined in the General Equal Treatment Act .

Your application

Please submit your application with complete documents, preferably without a photograph, through our application portal .

To apply, please submit the following documents: 

• cover letter;
• curriculum vitae; including publication list;
• research prospectus in which you outline your planned contribution to the theme and questions of the working group (maximum 1,000 words);
• one published piece of research;
• names and contact details of at least two referees. 

Please note that only complete electronic submissions uploaded to this link will be accepted. Applications sent via email will not be accepted. Applications may be submitted in English.

Applications must be received by  July 15, 2024 (23:45 CET).

Applications will be reviewed by late July 2024 and short-listed candidates will be interviewed by mid August 2024. Only successful candidates will be notified.

For questions concerning the working group and Department III, please contact Lisa Onaga .

For administrative questions concerning the position and the Institute, please contact Rand El Zein .

For technical questions regarding the application portal, please contact the Department secretary .

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