The document summarizes the findings of an HEA project on the challenges of assessment and feedback. It discusses various methods of technology-enhanced assessment including e-portfolios, peer assessment, MCQs, and self-assessment. It provides advice on how to design effective feedback and the importance of supporting students to act on feedback. Key messages emphasize that pedagogy is more important than technology, automated marking can be reliable, and staff development is essential.

1. The challenges of Assessment and Feedback: findings from an HEA project Denise Whitelock [email_address]

2. Outline e-Assessment Challenge Authentic assessment, e-portfolios Peer assessment MCQs and self-assessment Feedback Advice for Action

3. Project purpose in conjunction with Southampton University Consult the academic community on useful references Seminar series Survey Advisors Invited contributors Prioritise evidence-based references Synthesise main points For readers: Academics using technology enhancement for assessment and feedback Learning technologists Managers of academic departments

4. The e-Assessment Challenge Constructivist Learning – Push Institutional reliability and accountability – Pull .

5. www.storiesabout.com www.storiesabout.com/creativepdp [email_address]

6. Elliott’s characteristics of Assessment 2.0 activities Characteristics Descriptor Authentic Involving real-world knowledge and skills Personalised Tailored to the knowledge, skills and interests of each student Negotiated Agreed between the learner and the teacher Engaging Involving the personal interests of the students Recognise existing skills Willing to accredit the student’s existing work Deep Assessing deep knowledge – not memorization Problem oriented Original tasks requiring genuine problem solving skills Collaboratively produced Produced in partnership with fellow students Peer and self assessed Involving self reflection and peer review Tool supported Encouraging the use of ICT

7. Authentic assessments :e-portfolios Electronic NVQ portfolio cover contents page, OCR IT Practitioner, EAIHFE, Robert Wilsdon

8. Candidate Assessment Records section, OCR IT Practitioner, EAIHFE, Robert Wilsdon

9. Building e-portfolios on a chef’s course food preparation for e-portfolio, Modern Apprenticeship in Hospitality and Catering, West Suffolk College, Mike Mulvihill Evidence of food preparation skill for e-portfolio, Modern Apprenticeship in Hospitality and Catering, West Suffolk College, Mike Mulvihill

10. Sharing e-portfolios: The Netfolio concept Social constructivism Connecting e-portfolios (Barbera, 2009) Share and build upon a joint body of evidence Trialled with 31 PhD students at a virtual university Control group used but Netfolio group obtained higher grades Greater visibility of revision process and peer assessment in the Netfolio system

11. Peer Assessment and the WebPA Tool Loughborough (Loddington et al, 2009) Self assess and peer assess with given criteria Group mark awarded by tutor Students rated: More timely feedback Reflection Fair rewards for hard work Staff rated: Time savings Administrative gains Automatic calculation Students have faith in the administrative system

12. MCQs: Variation on a theme (1) The question is an example of a COLA assessment used at the Reid Kerr College, Paisley. It is a Multiple response Question used in one of their modules. The question was developed using Questionmark Perception at the University of Dundee. It is part a set of formative assessment for medical students.

13. MCQs: Variation on a theme (2) Example of LAPT Certainty-Based Marking, UK cabinet ministers demo exercise showing feedback, University College, Tony Gardner-Medwin Drug Chart Errors and Omissions, Medicines Administration Assessment, Chesterfield Royal Hospital

14. Scaffolding and High Stakes assessment Math for Science Tutor less course Competency led No point to cheat Web home exam Invigilation technologies

15. Self diagnosis Basic IT skills, first year med students (Sieber, 2009) Competency based testing Repeating tests for revision Enables remedial intervention

16. Students want more support with assessment More Feedback Quicker Feedback Full Feedback User friendly Feedback And ..................National Students’ Survey

17. Problems with Feedback Ignore feedback Look at the mark only Tells me correct solution but not what’s wrong with mine Needs decoding Timely

18. Gains from Interactivity with Feedback: Formative Assessment Mean effect size on standardised tests between 0.4 to 0.7 (Black & Williams, 1998) Particularly effective for students who have not done well at school http://kn.open.ac.uk/document.cfm?docid=10817 Can keep students to timescale and motivate them How can we support our students to become more reflective learners and enter a digitaldiscourse?

19. Mobile Technologies and Assessment MCQs ,PDAs Valdiva & Nussbaum(2009) Polls,instant surveys Simpson & Oliver (2007) Draper (2009) EVS

20. Collaborative formative assessment with Global Warming

21. Global Warming

22. Global Warming: Simlink Presentation

23. Next: ‘Yoked’ apps via BuddySpace Student A Student B (‘yoked’, but without full screen sharing required!)

24. Free Text Entry and Feedback LISC for languages Open Comment IAT for Science

25. LISC: Aily Fowler Kent University ab-initio Spanish module Large student numbers Skills-based course Provision of sufficient formative assessment meant unmanageable marking loads Impossible to provide immediate feedback leading to fossilisation of errors

26. The LISC solution: developed by Ali Fowler A CALL system designed to enable students to: Independently practise sentence translation Receive immediate (and robust) feedback on all errors Attend immediately to the feedback (before fossilisation can occur)

27. How is the final mark arrived at in the LISC System? The two submissions are un equally weighted Best to give more weight to the first attempt since this ensures that students give careful consideration to the construction of their first answer but can improve their mark by refining the answer The marks ratio can vary (depending on assessment/feedback type) the more information given in the feedback, the lower the weight the second mark should carry

28. Heuristics for the final mark If the ratio is skewed too far in favour of the first attempt… students are less inclined to try hard to correct non-perfect answers If the ratio is skewed too far in favour of the second attempt… students exhibit less care over the construction of their initial answer

29. Open Comment addresses the problem of free text entry Automated formative assessment tool Free text entry for students Automated feedback and guidance Open questions, divergent assessment No marks awarded For use by Arts Faculty

30. IAT (Jordan & Mitchell, 2009) Marking engine – Web service Authoring tool for marking rules for each question Model answers but free text entry by student Human computer marking comparisons indistinguishable at 1% level for two thirds of questions Problems question writing Human marking is inconsistent (Conole & Warburton, 2005)

31. Models of feedback which are open to test How would you instruct a robot to mark as you do?

32. Stages of analysis by computer of students’ free text entry for Open Comment: advice with respect to content (socio-emotional support stylised example) STAGE 1a: DETECT ERRORS E.g. Incorrect dates, facts. (Incorrect inferences and causality is dealt with below) Instead of concentrating on X, think about Y in order to answer this question Recognise effort (Dweck) and encourage to have another go You have done well to start answering this question but perhaps you misunderstood it. Instead of thinking about X which did not…….. Consider Y

33. Computer analysis continued STAGE 2a: REVEAL FIRST OMISSION Consider the role of Z in your answer Praise what is correct and point out what is missing Good but now consider the role X plays in your answer STAGE 2b: REVEAL SECOND OMISSION Consider the role of P in your answer Praise what is correct and point out what is missing Yes but also consider P. Would it have produced the same result if P is neglected?

34. Final stages of analysis STAGE 3:REQUEST CLARIFICATION OF KEY POINT 1 STAGE 4:REQUEST FURTHER ANALYSIS OF KEY POINT 1 (Stages 3 and 4 repeated with all the key points) STAGE 5:REQUEST THE INFERENCE FROM THE ANALYSIS OF KEY POINT 1 IF IT IS MISSING STAGE 6:REQUEST THE INFERENCE FROM THE ANALYSIS OF KEY POINT 1 IF IT IS NOT COMPLETE STAGE 7:CHECK THE CAUSALITY STAGE 8:REQUEST ALL THE CAUSAL FACTORS ARE WEIGHTED

35. McFeSPA system Supports teaching assistants to mark and give feedback on undergraduate computer programming assignments Support tool for semi-automated marking and scaffolding of feedback Findings that feedback model would be helpful in training tutors .... Similar to Open Comment findings

36. Feedback: Advice for Action Students must decode feedback and then act on it Boud (2000) Students must have the opportunity to act on feedback Sadler (1989) Gauging efficacy through student action Deep and strategic study approaches more effective in processing e-feedback Strang (2010)

37. Audio Feedback (Middleton & Nortcliffe, 2010) Timely and meaningful Manageable for tutors to produce and the learner to use Clear in purpose, adequately introduced and pedagogically embedded Technically reliable and not adversely determined by technical constraints or difficulties Targeted at specific students, groups or cohorts, addressing their needs with relevant points in a structured way Produced within the context of local assessment strategies and in combination, if appropriate, with other feedback methods using each medium to good effect Brief, engaging and clearly presented, with emphasis on key points that demand a specified response from the learner Of adequate technical quality to avoid technical interference in the listener’s experience Encouraging, promoting self esteem Formative, challenging and motivational

38. Elliott’s characteristics of Assessment 2.0 activities A d v i c e f o r A c t i o n Characteristics Descriptor Authentic Involving real-world knowledge and skills Personalised Tailored to the knowledge, skills and interests of each student Negotiated Agreed between the learner and the teacher Engaging Involving the personal interests of the students Recognise existing skills Willing to accredit the student’s existing work Deep Assessing deep knowledge – not memorization Problem oriented Original tasks requiring genuine problem solving skills Collaboratively produced Produced in partnership with fellow students Peer and self assessed Involving self reflection and peer review Tool supported Encouraging the use of ICT

39. Creating teaching and learning dialogues: towards guided learning supported by technology Learning to judge Providing reassurance Providing a variety of signposted routes to achieve learning goals

40. Key Messages Effective regular, online testing can encourage student learning and improve their performance in tests (JISC, 2008) Automated marking can be more reliable than human markers and there is no medium effect between paper and computerized exams ( Lee and Weerakoon, 2001) The success of assessment and feedback with technology-enhancement lies with the pedagogy rather than the technology itself; technology is an enabler (Draper, 2009)

41. Keys Messages 2 Technology-enhanced assessment is not restricted to simple questions and clear-cut right and wrong answers, much more sophisticated questions are being used as well (Whitelock & Watt, 2008) The design of appropriate and constructive feedback plays a vital role in the success of assessment, especially assessment for learning. ( Beaumont, O’Doherty & Shannon, 2008)

42. Key Messages 3 Staff development essential to the process (Warburton, 2009) Prepare students to take the assessments that use technology enhancement by practicing with similar levels of assessment using the same equipment and methods ( Shepherd et al, 2006) The reports generated by many technology-enhanced assessment systems are very helpful in checking the reliability and validity of each test item and the test as a whole can be checked on commercial systems ( McKenna and Bull, 2000)

43. References Beaumont, C., O’Doherty, M., and Shannon, L. (2008). Staff and student perceptions of feedback quality in the context of widening participation, Higher Education Academy. Retrieved May 2010 from: http://www.heacademy.ac.uk/assets/York/documents/ourwork/research/Beaumont_Final_Report.pdf. Draper, S. (2009). Catalytic assessment: understanding how MCQs and EVS can foster deep learning. British Journal of Educational Technology, 40 (2), 285-293. JISC, HE Academy, and ALT (2008). Exploring Tangible Benefits of e-Learning. Retrieved in May 2010 from http://www.jiscinfonet.ac.uk/publications/info/tangible-benefits-publication . Lee, G. and Weerakoon, P. (2001). The role of computer-aided assessment in health professional education: a comparison of student performance in computer-based and paper-and-pen multiple-choice tests. Medical Teacher, Vol 23 , No. 2, 152 - 157. McKenna, C. and Bull, J. (2000). Quality assurance of computer-assisted assessment: practical and strategic issues. Quality Assurance in Education. 8 (1), 24-31.

44. References 2 Middleton, A. and Nortcliffe, A. (2010) ‘Audio feedback design: principles and emerging practice’, In D.Whitelock and P.Brna (eds) Special Issue ‘Focusing on electronic feedback: feasible progress or just unfulfilled promises?’ Int. J. Continuing Engineering Education and Life-Long Learning, Vol. 20, No. 2, pp.208-223. Shephard, K., Warburton, B., Maier, P. and Warren, A. (2006). Development and evaluation of computer-assisted assessment in higher education in relation to BS7988. Assessment & Evaluation in Higher Education, 31 : 5, 583 — 595. Strang, K.D. (2010) ‘Measuring self regulated e-feedback, study approach and academic outcome of multicultural university students’, In D.Whitelock and P.Brna (eds) Special Issue ‘Focusing on electronic feedback: feasible progress or just unfulfilled promises?’ Int. J. Continuing Engineering Education and Life-Long Learning, Vol. 20, No. 2, pp.239-255. Warburton, B. (2009). Quick win or slow burn: modelling UK HE CAA uptake, Assessment & Evaluation in Higher Education, 34 : 3, 257 — 272. Whitelock, D. and Watt, S. (2008). Reframing e-assessment: adopting new media and adapting old frameworks. Learning, Media and Technology, Vol. 33, No. 3, September 2008, pp.153–156 Routledge, Taylor & Francis Group. ISSN 1743-9884

45. Three Assessment Special Issues Brna, P. & Whitelock, D. (Eds.) (2010) Special Issue of International Journal of Continuing Engineering Education and Life-long Learning, Focussing on electronic Feedback: Feasible progress or just unfulfilled promises? Volume 2, No. 2 Whitelock, D. (Ed.) (2009) Special on e-Assessment: Developing new dialogues for the digital age. Volume 40, No. 2 Whitelock, D. and Watt, S. (Eds.) (2008). Reframing e-assessment: adopting new media and adapting old frameworks. Learning, Media and Technology, Vol. 33 , No. 3