Skip to main content
SpringerLink
Log in

How Does Technology Enable Scaling Up Assessment for Learning?

  • Chapter
  • First Online:
Scaling up Assessment for Learning in Higher Education

Part of the book series: The Enabling Power of Assessment ((EPAS,volume 5))

Abstract

This chapter brings recent critical thought from the field of educational technology to bear on the challenge of scaling up Assessment for Learning (AfL). Three different types of ‘scaling up’ are presented, illustrated through three different ‘technology-enhanced’ AfL approaches. Recent advances in providing feedback through audio, video and screencast technologies are used to explore ‘doing more with less’ as a form of scaling up. Technology enables providing more and richer feedback information while requiring less staff time – but it remains unclear if this results in better learning or just better student experience. Technology’s ability to scale up our thinking from individual tasks up to programme level matters is explored through portfolios and curriculum mapping tools. Although these tools provide affordances for programmatic thinking, implementing these thoughts in the complex social environment of higher education presents its own challenges. Finally, scaling up AfL to serve large cohorts without linearly scaling up resources like teacher time is explored through Massive Open Online Courses (MOOCs). However, given the low completion rates in MOOCs, we question if access to AfL is the same as real AfL opportunity. The chapter concludes with implications for scaling up AfL that have been synthesized from these illustrative examples.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Bennett, S., Dawson, P., Bearman, M., Molloy, E., & Boud, D. (2016). How technology shapes assessment design: Findings from a study of university teachers. British Journal of Educational Technology. doi:10.1111/bjet.12439.

    Google Scholar 

  • Biggs, J. (1999). What the student does: Teaching for enhanced learning. Higher Education Research and Development, 18(1), 57–75.

    Article  Google Scholar 

  • Black, P., Harrison, C., Lee, C., Marshall, B., & Wiliam, D. (2004). Working inside the black box: Assessment for learning in the classroom. Phi Delta Kappan, 86(1), 8–21.

    Article  Google Scholar 

  • Black, P., & Wiliam, D. (1998). Assessment and classroom learning. Assessment in Education: Principles, Policy & Practice, 5(1), 7–74.

    Article  Google Scholar 

  • Blin, F., & Munro, M. (2008). Why hasn’t technology disrupted academics’ teaching practices? Understanding resistance to change through the lens of activity theory. Computers & Education, 50(2), 475–490.

    Article  Google Scholar 

  • Boud, D. (1995). How can self assessment be implemented? In D. Boud (Ed.), Enhancing learning through self-assessment (pp. 177–188). New York: Routledge Falmer.

    Google Scholar 

  • Boud, D. (2000). Sustainable assessment: Rethinking assessment for the learning society. Studies in Continuing Education, 22(2), 151–167.

    Article  Google Scholar 

  • Boud, D., & Molloy, E. (2012). Rethinking models of feedback for learning: The challenge of design. Assessment & Evaluation in Higher Education, 38(6), 698–712.

    Article  Google Scholar 

  • Carless, D. (2009). Trust, distrust and their impact on assessment reform. Assessment & Evaluation in Higher Education, 34(1), 79–89.

    Article  Google Scholar 

  • Carroll, D. (2014). Graduate course experience 2013: A report on the course experience perceptions of recent graduates. Melbourne, Australia: Graduate Careers Australia.

    Google Scholar 

  • Clark, R. C. (2010). Evidence-based training methods: A guide for training professionals. Alexandria, VA: American Society for Training & Development.

    Google Scholar 

  • Dawley, L., & Dede, C. (2014). Situated learning in virtual worlds and immersive simulations. In J. M. Spector, M. D. Merrill, J. Elen, & M. J. Bishop (Eds.), Handbook of research on educational communications and technology (pp. 723–734). New York: Springer.

    Chapter  Google Scholar 

  • Debuse, J. C. W., & Lawley, M. (2016). Benefits and drawbacks of computer-based assessment and feedback systems: Student and educator perspectives. British Journal of Educational Technology, 47(2), 294–301.

    Article  Google Scholar 

  • Deeley, S. J., & Bovill, C. (2016). Staff student partnership in assessment: Enhancing assessment literacy through democratic practices. Assessment & Evaluation in Higher Education. doi:10.1080/02602938.2015.1126551.

    Google Scholar 

  • Deneen, C., & Boud, D. (2013). Patterns of resistance in managing assessment change. Assessment & Evaluation in Higher Education, 39(5), 577–591.

    Article  Google Scholar 

  • Engstrom, C., & Tinto, V. (2008). Access without support is not opportunity. Change: The Magazine of Higher Learning, 40(1), 46–50.

    Article  Google Scholar 

  • Fawcett, H., & Oldfield, J. (2016). Investigating expectations and experiences of audio and written assignment feedback in first-year undergraduate students. Teaching in Higher Education, 21(1), 79–93.

    Article  Google Scholar 

  • Gasevic, D., Kovanovic, V., Joksimovic, S., & Siemens, G. (2014). Where is research on massive open online courses headed? A data analysis of the MOOC research initiative. The International Review of Research in Open and Distributed Learning, 15(5), 134–176.

    Article  Google Scholar 

  • Gikandi, J. W., Morrow, D., & Davis, N. E. (2011). Online formative assessment in higher education: A review of the literature. Computers & Education, 57(4), 2333–2351.

    Article  Google Scholar 

  • Hattie, J. (2009). The black box of tertiary assessment: An impending revolution. In L. H. Meyer, S. Davidson, H. Anderson, R. Fletcher, P. M. Johnston, & M. Rees (Eds.), Tertiary assessment & higher education student outcomes: Policy, practice & research. Ako Aotearoa: Wellington, New Zealand.

    Google Scholar 

  • Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81–112.

    Article  Google Scholar 

  • Henderson, M., & Phillips, M. (2015). Video-based feedback on student assessment: Scarily personal. Australasian Journal of Educational Technology, 31(1), 51–66.

    Google Scholar 

  • Higher Education Funding Council for England. (2014). UK review of the provision of information about higher education: National Student Survey results and trends analysis 2005–2013. London: HEFCE.

    Google Scholar 

  • Hollands, F. M., & Tirthali, D. (2014). MOOCs: Expectations and reality. New York: Center for Benefit-Cost Studies of Education, Teachers College, Columbia University.

    Google Scholar 

  • Johnson, L., Adams Becker, S., Cummins, M., Estrada, V., Freeman, A., & Hall, C. (2016). NMC horizon report: 2016 higher education edition. Austin, TX: The New Media Consortium.

    Google Scholar 

  • Joughin, G. (2009). Assessment, learning and judgement in higher education: A critical review. In G. Joughin (Ed.), Assessment, learning and judgement in higher education (pp. 13–27). Dordrecht, The Netherlands: Springer.

    Chapter  Google Scholar 

  • King, D., McGugan, S., & Bunyan, N. (2008). Does it make a difference? Replacing text with audio feedback. Practice and Evidence of Scholarship of Teaching and Learning in Higher Education, 3(2), 145–163.

    Google Scholar 

  • Laughton, D. J. (2013). Using audio feedback to enhance assessment practice – An evaluation of student and tutor perspectives. Student Engagement and Experience Journal.

    Google Scholar 

  • Laurillard, D. (2008). Digital technologies and their role in achieving our ambitions for education. London: Institute of Education.

    Google Scholar 

  • Lawson, R., Taylor, T., French, E., Fallshaw, E., Hall, C., Kinash, S., & Summers, J. (2015). Hunting and gathering: New imperatives in mapping and collecting student learning data to assure quality outcomes. Higher Education Research and Development, 34(3), 581–595.

    Article  Google Scholar 

  • Lefevre, D., & Cox, B. (2016). Feedback in technology-based instruction: Learner preferences. British Journal of Educational Technology, 47(2), 248–256.

    Article  Google Scholar 

  • Liu, N.-F., & Carless, D. (2006). Peer feedback: The learning element of peer assessment. Teaching in Higher Education, 11(3), 279–290.

    Article  Google Scholar 

  • Lunt, T., & Curran, J. (2010). ‘Are you listening please?’ The advantages of electronic audio feedback compared to written feedback. Assessment & Evaluation in Higher Education, 35(7), 759–769.

    Article  Google Scholar 

  • Macdonald, R., & Joughin, G. (2009). Changing assessment in higher education: A model in support of institution-wide improvement. In G. Joughin (Ed.), Assessment, learning and judgement in higher education (pp. 1–21). Dordrecht: Springer.

    Chapter  Google Scholar 

  • Marsh, E., Roediger, H., Bjork, R., & Bjork, E. (2007). The memorial consequences of multiple-choice testing. Psychonomic Bulletin & Review, 14(2), 194–199.

    Article  Google Scholar 

  • Means, B., Toyama, Y., Murphy, R., Bakia, M., & Jones, K. (2010). Evaluation of evidence-based practices in online learning: A meta-analysis and review of online learning studies. Report of U.S. Department of Education. Retrieved from https://www2.ed.gov/rschstat/eval/tech/evidence-based-practices/finalreport.pdf

  • Molloy, E., & Boud, D. (2014). Feedback models for learning, teaching and performance. In J. Spector, M. Merrill, J. Elen, & M. Bishop (Eds.), Handbook of research on educational communications and technology. New York: Springer Science+Business Media.

    Google Scholar 

  • Offerdahl, E. G., & Tomanek, D. (2011). Changes in instructors’ assessment thinking related to experimentation with new strategies. Assessment & Evaluation in Higher Education, 36(7), 781–795.

    Article  Google Scholar 

  • Oliver, M. (2011). Technological determinism in educational technology research: Some alternative ways of thinking about the relationship between learning and technology. Journal of Computer Assisted Learning, 27(5), 373–384.

    Article  Google Scholar 

  • Piech, C., Huang, J., Chen, Z., Do, C., Ng, A., & Koller, D. (2013). Tuned models of peer assessment in MOOCs. Paper presented at the 2013 Conference on Educational Data Mining, Memphis, TN.

    Google Scholar 

  • Posey, L., Plack, M. M., Snyder, R., Dinneen, P. L., Feuer, M., & Wiss, A. (2015). Developing a pathway for an institution wide ePortfolio program. International Journal of ePortfolio, 5(1), 75–92.

    Google Scholar 

  • Price, M., Rust, C., O'Donovan, B., & Handley, K. (2012). Assessment literacy: The foundation for improving student learning. Oxford, UK: Oxford Centre for Staff and Learning Development.

    Google Scholar 

  • Ramaprasad, A. (1983). On the definition of feedback. Behavioral Science, 28(1), 4–13.

    Article  Google Scholar 

  • Rhodes, T., Chen, H. L., Watson, C. E., & Garrison, W. (2014). Editorial: A call for more rigorous ePortfolio research. International Journal of ePortfolio, 4(1), 1–15.

    Google Scholar 

  • Russell, T. (2013). The no significant difference phenomenon. Retrieved from http://www.nosignificantdifference.org/

  • Sadler, D. R. (1989). Formative assessment and the design of instructional systems. Instructional Science, 18(2), 119–144.

    Article  Google Scholar 

  • Selwyn, N. (2010). Looking beyond learning: Notes towards the critical study of educational technology. Journal of Computer Assisted Learning, 26(1), 65–73.

    Article  Google Scholar 

  • Selwyn, N. (2011). In praise of pessimism—the need for negativity in educational technology. British Journal of Educational Technology, 42(5), 713–718.

    Article  Google Scholar 

  • Stödberg, U. (2012). A research review of e-assessment. Assessment & Evaluation in Higher Education, 37(5), 591–604.

    Article  Google Scholar 

  • Tamim, R. M., Bernard, R. M., Borokhovski, E., Abrami, P. C., & Schmid, R. F. (2011). What forty years of research says about the impact of technology on learning. Review of Educational Research, 81(1), 4–28.

    Article  Google Scholar 

  • Tomas, C., Borg, M., & McNeil, J. (2015). E-assessment: Institutional development strategies and the assessment life cycle. British Journal of Educational Technology, 46(3), 588–596.

    Article  Google Scholar 

  • University of Minnesota. (2016). Hype Cycle for Education: Emerging Technologies in Higher Education. Retrieved from http://hypecycle.umn.edu/page/what-hype-cycle

  • Warburton, B. (2009). Quick win or slow burn: Modelling UK HE CAA uptake. Assessment & Evaluation in Higher Education, 34(3), 257–272.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Deakin University, Burwood, VIC, Australia

    Phillip Dawson

  2. Faculty of Education, Monash University, Melbourne, VIC, Australia

    Michael Henderson

Authors
  1. Phillip Dawson
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Michael Henderson
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Phillip Dawson .

Editor information

Editors and Affiliations

  1. Faculty of Education, University of Hong Kong, Hong Kong, Hong Kong

    David Carless

  2. Faculty of Education, University of Hong Kong, Hong Kong, Hong Kong

    Susan M. Bridges

  3. Ctr. Enhancement of Teaching & Learning, University of Hong Kong, Hong Kong, Hong Kong

    Cecilia Ka Yuk Chan

  4. Faculty of Law, University of Hong Kong, Hong Kong, Hong Kong

    Rick Glofcheski

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer Nature Singapore Pte Ltd.

About this chapter

Cite this chapter

Dawson, P., Henderson, M. (2017). How Does Technology Enable Scaling Up Assessment for Learning?. In: Carless, D., Bridges, S., Chan, C., Glofcheski, R. (eds) Scaling up Assessment for Learning in Higher Education. The Enabling Power of Assessment, vol 5. Springer, Singapore. https://doi.org/10.1007/978-981-10-3045-1_14

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-3045-1_14

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3043-7

  • Online ISBN: 978-981-10-3045-1

  • eBook Packages: EducationEducation (R0)

Publish with us

Policies and ethics

Search

Navigation