Computer Science

Lectures: COMPSCI 747 Semester 1, City Campus

Lecture outline and resources

Introduction to Computing Education Research. The first section provides an overview of Education theory, methodologies for conducting research, ways of analysing data, and evaluating the quality and success of research.

1. Introduction. What is Computer Science?

What is the core of a Computer Science programme and how does it differ from Software Engineering and Information Technology programmes? Understanding the ACM/IEEE curriculum documents.

Learning outcome:: Describe what Computer Science is, using only two sentences.

2. Educational Orientations

An overview of many of the main theories in Education. Constructivism, Cognitivism, Social Cognitive Theory

Learning outcomes:: Recognize the application of a learning theory in an educational context; Use a learning theory in the design of an educational task

3. Do people struggle to learn programming?

An overview of the novice programming literature

Learning outcomes:: Describe the main evidence for difficulty in programming

4. Learning Edge Momentum

A recent theory that attempts to explain why novices struggle to learn programming

Robins, Learning Edge Momentum [Required]

Learning outcomes:: Describe and critically reflect on the learning edge momentum theory.

5. Case study: PeerWise as a collaborative learning tool (Monday 16th March)

Lecture slides

The "generation" effect

Bertsch et al., The generation effect: A meta-analytic review Memory & Cognition, 2007, 35(2), pp 201-210
Foos et al., Student study techniques and the generation effect Journal of Educational Psychology, 1994, 86(4), pp 567-576

The "self-explanation" effect

Kwon et al., Self-explanation prompts on problem-solving performance in an interactive learning environment Journal of Interactive Online Learning, 2011, 10(2)
Aleven and Koedinger, An effective metacognitive strategy: learning by doing and explaining with a computer-based Cognitive Tutor Cognitive Science, 2002, 26, pp 147-179

The "testing" effect

Roediger and Butler, Retrieval practice (testing) effect In H. L. Pashler (Ed.), Encyclopedia of the Mind, 2013, Sage Publishing Co., California, pp 660-661
Karpicke and Roediger, The Critical Importance of Retrieval for Learning, Science, 2008, 319, pp 966-968

Denny et al., The PeerWise System of Student Contributed Assessment Questions, 2008, Proc. ACE '08, Australian Computer Society, pp 69-74

Learning outcome:: Explain the pedagogical motivations for an activity involving student-generated questions, identify potential problems and difficulties with this approach, and describe a tool that supports this activity.

6. Student generated learning resources - research examples (Friday 20th March)

Lecture slides

Denny, Generating Practice Questions as a Preparation Strategy for Introductory Programming Exams, 2015, Proc. SIGCSE 2015. ACM, pp 278-283 [required reading]
Bottomley et al., A Participatory Learning Approach to Biochemistry Using Student Authored and Evaluated Multiple-choice Questions Biochemistry and Molecular Biology Education, 2011, 39(5), pp 352-361
Bates et al., Assessing the quality of a student-generated question repository 2014, Physics Review Special Topics, Physics Education Research, Vol. 10
Hardy et al., Student-Generated Content: Enhancing learning through sharing multiple-choice questions International Journal of Science Education, 2014, 36(13), pp 2180-2194
McQueen et al., PeerWise Provides Significant Academic Benefits to Biological Science Students Across Diverse Learning Tasks, But with Minimal Instructor Intervention Biochemistry and Molecular Biology Education, 2014

Learning outcome:: Activities in which students generate learning resources can been evaluated in various ways. Examples include assessing the quality of the resources and measuring the educational impact of the activities. For both of these examples, describe one study you are familiar with and comment critically on the methodology and results.

7. Gamification (Monday 23rd March)

Lecture slides

Deterding et al., From game design elements to gamefulness: defining "gamification" 2011, Proc. MindTrek'11, Tampere, Finland
Deterding, Gamification: designing for motivation Interactions, 2012, 19(4), pp14-17
Antin and Churchill Badges in social media : A social psychological perspective 2011, Proc. CHI 2011, Vancouver, pp 1-4
Denny, The effect of virtual achievements on student engagement 2013, Proc. CHI 2013, Paris, France, pp 763-772
Farzan et al., Results from deploying a participation incentive mechanism within the enterprise 2008, Proc. CHI 2008, Florence, Italy, pp 563-572
Andersen et al., On the harmfulness of secondary game objectives 2011, Proc. FDG 2011, Bordeaux, France, pp 30-37

Learning outcome:: Give a widely accepted definition for "gamification" and briefly describe the methods and results of one study examining the impact of gamification on user/student participation.

8. Contributing Student Pedagogy + Asst Two (Friday 27th March)

Lecture slides

Hamer, Some Experiences With The "Contributing Student Approach" 2006, Proc. ITiCSE'06, Bologna, Italy, pp 68-72
Collis and Moonen, The contributing student: Learners as co-developers of learning resources for reuse in web environments 2006, In Engaged Learning with Emerging Technologies, D. Hung and M.S. Khine (eds.), pp 49-67
Hamer et al., Tools for "contributing student learning" ACM Inroads, 2011, 2(2), pp 78-91
Luxton-Reilly et al., Constructive evaluation: a pedagogy of student-contributed assessment 2010, Computer Science Education, 20(2), pp 145-167
Hamer et al., Editorial - Contributing student pedagogy, Special Edition of Computer Science Education 2012, Computer Science Education, 22(4), pp 315-318
Falkner and Falkner, Supporting and structuring "contributing student pedagogy" in Computer Science curricula 2012, Computer Science Education, 22(4), pp 413-443
Herman, Designing contributing student pedagogies to promote students' intrinsic motivation to learn 2012, Computer Science Education, 22(4), pp 369-388
Denny et al., CodeWrite: Supporting Student-Driven Practice of Java 2011, Proc. SIGCSE'11, Dallas, pp 471-476
Peer review evaluation:

Reily et al., Two peers are better than one: aggregating peer reviews for computing assignments is surprisingly accurate 2009, Proc. GROUP'09, Florida, pp 115-124 [required reading]

Learning outcome:: Describe what is meant by a contributing student pedagogy (CSP), and identify some benefits and challenges of its implementation. Give several concrete examples of CSP activities.

9. Peer review + Evaluating CSP (Monday 30th March)

Lecture slides

Reily et al., Two peers are better than one: aggregating peer reviews for computing assignments is surprisingly accurate 2009, Proc. GROUP'09, Florida, pp 115-124 [required reading]
Falchikov and Goldfinch, Student Peer Assessment in Higher Education: A meta-analysis comparing peer and teacher marks 2000, Review of Educational Research, 70(3), pp 287-322
Hamer et al., Quality of peer assessment in CS1 2009, Proc. ICER'09, Berkeley, California, pp 27-36
Luxton-Reilly, A systematic review of tools that support peer assessment 2009, Computer Science Education, 19(4), pp 209-232
Bates et al., Assessing the quality of a student-generated question repository 2014, Physics Review Special Topics, Physics Education Research, Vol. 10
Denny et al., Understanding the syntax barrier for novices 2011, Proc. ITiCSE'11, Darmstadt, Germany, pp 208-212
Denny et al., CodeWrite: Supporting student driven practice of Java 2011, Proc. SIGCSE'11, Dallas, Texas, pp 471-476

Learning outcome:: Compare peer assessment with more traditional marking and discuss both advantages and disadvantages of the peer approach. Describe the methodology and results of a study in which the impact of peer assessment was investigated in a computer science course, and summarise the conclusions.

3. Learning Outcomes

What are learning outcomes and how can we write them? The idea of constructive alignment. Writing assessments.

Constructive alignment and instructional design [Required]

Learning outcome:: Write the learning outcomes appropriate for a given educational task

Research methodologies

An overview of quantitative, qualitative and mixed method studies. Specific methodologies of Case Study, Grounded theory, Ethnography, Action Research, Phenomenography, Discourse Analysis and Narrative Analysis are discussed.

Learning outcome:: Compare and contrast different research methodologies.

Outreach / CS Unplugged

How can Computer Science concepts be explained to children?

Learning outcome:: Describe some of the CS Unplugged activities

Analysing data

Comparing Qualitative and Quantitative methods. Reliability and Validity. Threats to validity

Learning outcome:: Critically evaluate methodologies, validity and reliability used in research papers.

Literature reviews

Some comments on Literature Reviews

Kitchenham, Brereton and Budgen The Educational Value of Mapping Studies of Software Engineering Literature ICSE 2010
Randolph A Guide to Writing the Dissertation Literature Review Practical Assessment, Research & Evaluation, 14 (13), 2009
Okoli, Chitu and Schabram, Kira A Guide to Conducting a Systematic Literature Review of Information Systems Research (May 5, 2010). Available at SSRN: http://ssrn.com/abstract=1954824 or http://dx.doi.org/10.2139/ssrn.1954824

Debugging

23. Code Complexity

Ethics and Ethical Issues

Human Participant Ethics Committee

Examine the guiding principles and the Applicants manual

Learning outcome:: Identify ethical issues with a particular study

Women in Computing

Learning from Pair Programming

Degree to which programming constructs are interconnected

Novice Debugging Processes

Computing for Social Good

Physical Games for Teaching CS

Literature review (including refs)

Computer Science

Lectures: COMPSCI 747 Semester 1, City Campus

Lecture outline and resources

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