Assessment as, for, and of Twenty-First Century Learning Using Information Technology: An Overview

  • Mary WebbEmail author
  • Dirk Ifenthaler
Reference work entry
Part of the Springer International Handbooks of Education book series (SIHE)


IT-based assessment has been advancing rapidly, and its growth is set to accelerate with emerging opportunities for automatic data collection as well as increased possibilities of communication and interaction mediated by IT. In this chapter we aim to present an overview of the range of different opportunities for IT to support assessment. We identify and discuss challenges for moving toward a situation where IT-based assessment can serve learners’ needs as well as the broader needs of the educational system for evaluation. We examine theories related to assessment more generally as well as specifically to IT-enabled assessment and review recent research and development. Scenarios for IT-enabled assessments may take many different forms, some of which hold much promise for supporting learning, but there are theoretical, developmental, technical, and human challenges to be overcome. Our vision is for IT-based assessment design to move forward with designers, teachers, and learners working together to design assessments that support twenty-first-century curricula and pedagogy. In this shared endeavor, we expect that data can be collected and represented to enable learners and teachers to identify achievements; collate evidence of those achievements; diagnose needs, both cognitive and affective; and decide on suitable pedagogical approaches for enabling the next steps in learning. We argue that open assessment resources provide a vehicle for enabling the large-scale developments that are needed to support the development of IT-enabled assessment across the broad spectrum of learning. Some of the more complex twenty-first-century skills of collaboration, problem-solving, critical thinking, etc. present particular challenges. We envisage that it may take many years for our vision to be realized. In the medium term, the need is to integrate IT-enabled assessments where appropriate alongside more traditional methods including teacher assessment.


Formative assessment Summative assessment Self regulated learning IT-enabled assessment Feedback Analytics 


  1. Abramovich, S., Schunn, C., & Higashi, R. M. (2013). Are badges useful in education?: It depends upon the type of badge and expertise of learner. Educational Technology Research and Development, 61(2), 217–232. Scholar
  2. Ahmed, A., & Pollitt, A. (2010). The support model for interactive assessment. Assessment in Education: Principles, Policy & Practice, 17(2), 133–167.CrossRefGoogle Scholar
  3. Assessment Reform Group, A. (2002). Assessment for Learning: 10 Principles.
  4. Bellotti, F., Kapralos, B., Lee, K., Moreno-Ger, P., & Berta, R. (2013). Assessment in and of serious games: An overview. Advances in Human-Computer Interaction, 2013, 1–11. Scholar
  5. Bennett, R. E. (2011). Formative assessment: A critical review. Assessment in Education: Principles, Policy & Practice, 18(1), 5–25.CrossRefGoogle Scholar
  6. Bennett, R. E. (2015). The changing nature of educational assessment. Review of Research in Education, 39(1), 370–407. Scholar
  7. Black, P. (2012). Formative and summative aspects of assessment: Theoretical and research foundations in the context of pedagogy. In SAGE handbook of research on classroom assessment (p. 167). London: SAGE.Google Scholar
  8. Black, P. (2015). Formative assessment – An optimistic but incomplete vision. Assessment in Education: Principles, Policy & Practice, 22(1), 161–177. Scholar
  9. Black, P., & Wiliam, D. (1998). Assessment and classroom learning. Assessment in Education, 5(1), 7–74.CrossRefGoogle Scholar
  10. Black, P., & Wiliam, D. (2009). Developing the theory of formative assessment. Educational Assessment, Evaluation and Accountability, 21, 5–31. Scholar
  11. Brown, G. T. L., & Gao, L. (2015). Chinese teachers’ conceptions of assessment for and of learning: Six competing and complementary purposes. Cogent Education, 2(1), 993836. Scholar
  12. Carless, D., & Lam, R. (2014). Developing assessment for productive learning in Confucian-influenced settings. In C. Wyatt-Smith, V. Klenowski, & P. Colbert (Eds.), Designing assessment for quality learning (pp. 167–179). Dordrecht: Springer Netherlands.CrossRefGoogle Scholar
  13. Chan, C. K. (2012). Co-regulation of learning in computer-supported collaborative learning environments: A discussion. Metacognition and Learning, 7(1), 63–73. Scholar
  14. Chang, H. Y., Wang, C. Y., Lee, M. H., Wu, H. K., Liang, J. C., Lee, S. W. Y., ... Tsai, C. C. (2015). A review of features of technology-supported learning environments based on participants’ perceptions. Computers in Human Behavior, 53, 223–237.
  15. Cheng, M. (2016). Strategies for introducing the particle view of matters: Cognitive conflicts, practical activities, multiple representations and assessment for learning. Paper presented at the East-Asian Association for Science Education Conference, Tokyo, 26th–28th August.Google Scholar
  16. Coll, C., Rochera, M. J., & de Gispert, I. (2014). Supporting online collaborative learning in small groups: Teacher feedback on learning content, academic task and social participation. Computers & Education, 75, 53–64. Scholar
  17. Cross, S., Whitelock, D., & Galley, R. (2014). The use, role and reception of open badges as a method for formative and summative reward in two massive open online courses. International Journal of e-Assessment, 4(1).
  18. Dann, R. (2014). Assessment as learning: Blurring the boundaries of assessment and learning for theory, policy and practice. Assessment in Education: Principles, Policy & Practice, 21(2), 149–166. Scholar
  19. Dewey, J. (1913). Interest and effort in education. Boston: Houghton Mifflin.CrossRefGoogle Scholar
  20. Dweck, C. S. (2000). Self-theories: Their role in motivation, personality and development. London: Taylor & Francis.Google Scholar
  21. Fulton, B. A. (2016). The relationship between test anxiety and standardized test scores. (PhD), Walden University, Retrieved from
  22. Gibson, D. C., & Webb, M. E. (2015). Data science in educational assessment. Education and Information Technologies, 20(4), 697–713. Scholar
  23. Gibson, D. C., Webb, M. E., & Forkosh-Baruch, A. (2012). Global perspectives on information and communications technology and educational assessment. Paper presented at the IFIP Working Conference: Addressing educational challenges – The role of ICT, Manchester Metropolitan University, Manchester.Google Scholar
  24. Gibson, D., Ostashewski, N., Flintoff, K., Grant, S., & Knight, E. (2013). Digital badges in education. Education and Information Technologies, 20(2), 403–410. Scholar
  25. Gibson, D. C., Ifenthaler, D., & Orlic, D. (2016). Open assessment resources for deeper learning. In P. Blessinger & T. J. Bliss (Eds.), Open education: International perspectives in higher education (pp. 257–279). Cambridge: Open Book Publishers.Google Scholar
  26. Hadwin, A. F., Oshige, M., Gress, C. L. Z., & Winne, P. H. (2010). Innovative ways for using gStudy to orchestrate and research social aspects of self-regulated learning. Computers in Human Behavior, 26, 794–805.CrossRefGoogle Scholar
  27. Harlen, W., & Deakin Crick, R. (2002). A systematic review of the impact of summative assessment and tests on students’ motivation for learning. Retrieved from London:
  28. Harlen, W., & James, M. (1997). Assessment and learning: Differences and relationships between formative and summative assessment. Assessment in Education: Principles, Policy & Practice, 4(3), 365–379. Scholar
  29. Hattie, J. A. C. (2009). Visible learning: A synthesis of over 800 meta-analyses relating to achievement. Abingdon: Routledge.Google Scholar
  30. Ifenthaler, D. (2012). Determining the effectiveness of prompts for self-regulated learning in problem-solving scenarios. Journal of Educational Technology & Society, 15(1), 38–52.Google Scholar
  31. Ifenthaler, D. (2014). Toward automated computer-based visualization and assessment of team-based performance. Journal of Educational Psychology, 106(3), 651–665. Scholar
  32. Ifenthaler, D. (2015). Learning analytics. In J. M. Spector (Ed.), The SAGE encyclopedia of educational technology (Vol. 2, pp. 447–451). Thousand Oaks: Sage.Google Scholar
  33. Ifenthaler, D., Pirnay-Dummer, P., & Seel, N. M. (Eds.). (2010). Computer-based diagnostics and systematic analysis of knowledge. New York: Springer.Google Scholar
  34. Järvelä, S., & Hadwin, A. F. (2013). New frontiers: Regulating learning in CSCL. Educational Psychologist, 48(1), 25–39.CrossRefGoogle Scholar
  35. Jarvela, S., Jarvenoja, H., & Veermans, M. (2008). Understanding the dynamics of motivation in socially shared learning. International Journal of Educational Research, 47(2), 122–135.CrossRefGoogle Scholar
  36. Johnson, W. L., & Lester, J. C. (2016). Face-to-face interaction with pedagogical agents, twenty years later. International Journal of Artificial Intelligence in Education, 26(1), 25–36. Scholar
  37. Jovanovic, J., & Devedzic, V. (2015). Open badges: Novel means to motivate, scaffold and recognize learning. Technology, Knowledge and Learning, 20(1), 115. Scholar
  38. Kizilcec, R. F., Pérez-Sanagustín, M., & Maldonado, J. J. (2017). Self-regulated learning strategies predict learner behavior and goal attainment in massive open online courses. Computers & Education, 104, 18–33. Scholar
  39. Lee, I., & Coniam, D. (2013). Introducing assessment for learning for EFL writing in an assessment of learning examination-driven system in Hong Kong. Journal of Second Language Writing, 22(1), 34–50. Scholar
  40. Lenhard, W., Baier, H., Hoffmann, J., & Schneider, W. (2007). Automatic scoring of constructed-response items with latent semantic analysis. Diagnostica, 53(3), 155–165. Scholar
  41. Mah, D.-K., Bellin-Mularski, N., & Ifenthaler, D. (2016). Moving forward with digital badges in education. In D. Ifenthaler, N. Bellin-Mularski, & D.-K. Mah (Eds.), Foundations of digital badges and micro-credentials (pp. 511–517). New York: Springer.CrossRefGoogle Scholar
  42. Messick, S. (1994). The interplay of evidence and consequences in the validation of performance assessments. Educational Researcher, 23(2), 13–23. Scholar
  43. Mislevy, R. J., Steinberg, L. S., & Almond, R. G. (2003a). On the structure of educational assessment. Measurement: Interdisciplinary Research and Perspective, 1(1), 3–62.Google Scholar
  44. Mislevy, R. J., Almond, R. G., & Lukas, J. F. (2003b). A Brief Introduction to Evidence-Centered Design. ETS Research Report Series, 2003(1), i–29.
  45. Ozel, M., Caglak, S., & Erdogan, M. (2013). Are affective factors a good predictor of science achievement? Examining the role of affective factors based on PISA 2006. Learning and Individual Differences, 24, 73–82. Scholar
  46. Perrenoud, P. (1998). From formative assessment to a controlled regulation of learning processes. Towards a wider conceptual field. Assessment in Education, 5(1), 85–102. Scholar
  47. Pintrich, P. R. (2000). The role of goal orientation in self-regulated learning. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 451–502). San Diego: Academic.CrossRefGoogle Scholar
  48. PISA. (2017). PISA 2015 Collaborative Problem-Solving Framework. Retrieved from
  49. Puzziferro, M. (2008). Online technologies self-efficacy and self-regulated learning as predictors of final grade and satisfaction in college-level online courses. American Journal of Distance Education, 22(2), 72–89. Scholar
  50. Rissanen, M. J., Kume, N., Kuroda, Y., Kuroda, T., Yoshimura, K., & Yoshihara, H. (2008). Asynchronous teaching of psychomotor skills through VR annotations: Evaluation in digital rectal examination. Studies in Health Technology and Informatics, 132, 411–416.Google Scholar
  51. Sadler, D. R. (2010). Beyond feedback: Developing student capability in complex appraisal. Assessment & Evaluation in Higher Education, 35(5), 535–550. Scholar
  52. Shulman, L. (1986). Those who understand: Knowledge growth in teaching. Educational Researcher, 15(2), 4–14.CrossRefGoogle Scholar
  53. Shute, V. J. (2011). Stealth assessment in computer-based games to support learning. In S. Tobias & J. D. Fletcher (Eds.), Computer games and instruction (pp. 503–524). Charlotte: Information Age Publishers.Google Scholar
  54. Shute, V. J., Leighton, J. P., Jang, E. E., & Chu, M.-W. (2016). Advances in the science of assessment. Educational Assessment, 21(1), 34–59. Scholar
  55. Stiggins, R. J. (1995). Assessment literacy for the 21st century. Phi Delta Kappan, 77, 238–245.Google Scholar
  56. Stödberg, U. (2012). A research review of e-assessment. Assessment & Evaluation in Higher Education, 37(5), 591–604. Scholar
  57. Suen, H. K. (2014). Peer assessment for massive open online courses (MOOCs). The International Review of Research in Open and Distributed Learning, 15(3), 312.CrossRefGoogle Scholar
  58. Turkay, S., & Tirthali, D. (2010). Youth leadership development in virtual worlds: A case study. Procedia – Social and Behavioral Sciences, 2(2), 3175–3179. Scholar
  59. Ucan, S., & Webb, M. E. (2015). Social regulation of learning during collaborative inquiry learning in science: How does it emerge and what are its functions? International Journal of Science Education, 37, 2503. Scholar
  60. Voogt, J., Erstad, O., Dede, C., & Mishra, P. (2013). Challenges to learning and schooling in the digital networked world of the 21st century. Journal of Computer Assisted Learning, 29(5), 403–413. Scholar
  61. Vygotsky, L. S. (1986). Thought and language. Cambridge, MA: MIT Press.Google Scholar
  62. Webb, M. E. (2010). Beginning teacher education and collaborative formative e-assessment. Assessment and Evaluation in Higher Education, 35(5), 597–618.CrossRefGoogle Scholar
  63. Webb, M. E. (2014). Pedagogy with information and communications technologies in transition. Education and Information Technologies, 19(2), 275–294. Scholar
  64. Webb, M. E., & Gibson, D. C. (2015). Technology enhanced assessment in complex collaborative settings. Education and Information Technologies, 20(4), 675–695. Scholar
  65. Webb, M. E., & Jones, J. (2009). Exploring tensions in developing assessment for learning. Assessment in Education: Principles, Policy & Practice, 16(2), 165–184. Scholar
  66. Webb, M. E., Gibson, D. C., & Forkosh-Baruch, A. (2013). Challenges for information technology supporting educational assessment. Journal of Computer Assisted Learning, 29(5), 451–462. Scholar
  67. Wiliam, D. (2011). What is assessment for learning? Studies In Educational Evaluation, 37(1), 3–14. Scholar
  68. Wiliam, D., & Thompson, M. (2007). Integrating assessment with instruction: What will it take to make it work? In C. A. Dwyer (Ed.), The future of assessment: Shaping teaching and learning (pp. 53–82). Mahwah: Lawrence Erlbaum Associates.Google Scholar
  69. Winne, P. H., & Hadwin, A. F. (2008). The weave of motivation and self-regulated learning. Motivation and self-regulated learning: Theory, research, and applications (pp. 297–0314). Mahwah: Lawrence Erlbaum Associates.Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.King’s College LondonLondonUK
  2. 2.Learning, Design and TechnologyUniversity of MannheimMannheimGermany
  3. 3.Curtin UniversityBentleyAustralia

Section editors and affiliations

  • Mary Webb
    • 1
  • Dirk Ifenthaler
    • 2
  1. 1.King's College LondonLondonUK
  2. 2.University of MannheimMannheimGermany

Personalised recommendations