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Enhancing Tutor Feedback with OpenMentor: A Free Mentoring Tool for Educators

OpenMentor is an open-source mentoring tool designed to improve the quality of feedback given by tutors to students on assignments. Developed by Denise Whitelock and Stuart Watt, it categorizes comments into four main groups: positive reactions, directing/teaching, questions, and negative reactions. The tool uses data from Open University courses to model effective tutor feedback practices. It emphasizes the need for detailed comments on lower grades while promoting positive feedback on higher scores. OpenMentor aims to integrate seamlessly into institutional infrastructures, enhancing educational quality through better mentoring.

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Enhancing Tutor Feedback with OpenMentor: A Free Mentoring Tool for Educators

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  1. Sponsored by JISC Conference 2006 OpenMentor Joint Information Systems Committee Supporting education and research

  2. OpenMentor: Opening tutors’ eyes to the written support given to students on their assignments Denise Whitelock, The Open University. d.m.whitelock@open.ac.uk Stuart Watt, Robert Gordon University s.n.k.watt@rgu.ac.uk

  3. What is OpenMentor? • “An open source mentoring tool for tutors” • “Open source” = free and easy to use, and to embed in an institutions infrastructure and working practices • “mentoring” = designed to help people learn how to give feedback effectively, through reflection and social networks • “tutors” = primarily intended for teaching staff, but with clear applications for those involved in quality

  4. How does it work? • Codes comments into Bales categories • Four main groupings • A. Positive reactions • B. Directing/teaching • C. Questions • D. Negative reactions

  5. Coding the comments

  6. Does OpenMentor model the way tutors comment on assignments? • Data derived from OU courses • Categories: • A = positive reactions • B = attempted answers • C = questions • D = negative reactions • A, B, C correlations all statistically significant • This forms an implicit model of good practice in tutor feedback

  7. Does OpenMentor work in the way tutors and students expect? • 46 students and 44 tutors responded to a questionnaire to test OM’s underlying tutorial model • Findings suggest: • Lower grades should attract more detailed comments and explanation by the tutor (students) • Higher grades should attract more positive comments (students and tutors) • Lower grades attract more questions and suggestions (tutors) • Model supported by pedagogical study

  8. “Good work” “Yes, well done” “Yes, but is this useful?” “Can you explain what you mean” “This does not follow” A = positive reactions A = positive reactions B = attempted answers, and not a positive reaction C = questions D = negative reactions How Open Mentor handles comments

  9. OpenMentor in action Demonstration

  10. Inside Open Mentor Bench- marks Course info Web interface Analyser Assess- ments Extractor Classifier

  11. Current and future developments • Embedding in institutional practice • Enhancing quality of first year provision • Links to VLEs and information systems • Spinning out components • Word text extraction (Apache POI) • Uptake of open source • Maven, Spring, Subversion, Hibernate • Further development • Support for students, course evaluation, etc…

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