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Progress when Programming
Transcript of Progress when Programming
16th March 2011 Facilitating learning of computer programming through diagnostic and formative assessment. Option 5 — Do you see opportunities for innovative assessment methods in the modules that you have been involved in supporting or are the current methods still fit for purpose? Programming at York Mathematics Computer Science Biology Physics Electronics ...? Learning outcomes (illustrative) Write programs in a particular programming language.
Select and apply appropriate algorithms and data structures to problems.
Analyse program performance, theoretically and empirically.
Extend existing programs and apply professional standards to produce reusable and extendable code.
Determine correctness conditions and devise effective testing strategies.
Leverage software development and professional tools. What the people say "Assessments take too long to mark." – PTA "Unclear as to what level of commenting will be deemed acceptable." – Student "Exercises are pointlessly repetitive." – Student "I find it intimidating to ask questions when everyone else seems to be getting on OK." – Student "I think the class is getting on ok." – PTA Suggestions Peer assessment Reusability & collaboration. Fine-grained, frequent & automated. Professional Skills Produce products and adapt to changes quickly.
Get immediate feedback on progress.
Get feedback on things that matter.
Learn by making mistakes.
Save effort and interest by not having to "reinvent the wheel."
Tools exist for support the methodology. Formative/Diagnostic assessment Summative assessment Guides learning Forces learning (Bloom et. al. 1971) Formative assessment strategies Guided self-assessment Formal submitted assessment Exercises done in compulsory labs.
Lecturer and PGWTs observe.
Students regularly given solutions. Exercises are completed in labs or at home.
Deadlines are set for handins.
Pressurised. Two extremes "Undoubtedly, programming is best learned through practice." (Sayers, Nicell and Haga, 2004) (Jenkins 2001) Fine-grained, frequent and automated Helps students track their own progress.
Removes fear of failure as it becomes part of the learning process.
Anytime / anywhere. Not all the learning objectives can be assessed automatically.
These (e.g. analysis and communication skills) are social and subjective.
Peer assessment can help develop this skills and track progress. Peer assessment (Bhalerao & Ward, 2001) Reusability & collaboration Building towards a greater goal.
Occasionally release model solutions.
A variety of individual but connected component exercises which individual students can combine to observe greater results. References Bloom, Madaus & Hastings. Handbook on Formative and Summative Evaluation of Student Learning. 1971 Sayers, Nicell & Haga. Supporting and Assessing First Year Programming: The Use of WebCT. 2004 Jenkins. Teaching Programming – A Journey from Teacher to Motivator. 2001 Coleman & Nichols. Embedding Inquiry based learning into Programming via Paired Assessment. 2011. Bhalerao & Ward. Towards Electronically Assisted Peer Assessment: a case study. 2001. Results, Conclusions and Further work Fine-grained assessments, offline automated testing and reusable components have been tried and have had generally positive feedback.
Other techniques require more infrastructure to test.
Constructive alignment runs deep. Going back to the beginning may give you the solutions you need. Find me at http://bit.ly/JasonPFA