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Involvement of Learners’ Characteristics within the Allocation of Submissions in the context of Peer Assessment in MOOCs

by M. A. Abrache, A. Qazdar, C. Cherkaoui
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 168 - Number 12
Year of Publication: 2017
Authors: M. A. Abrache, A. Qazdar, C. Cherkaoui
10.5120/ijca2017914507

M. A. Abrache, A. Qazdar, C. Cherkaoui . Involvement of Learners’ Characteristics within the Allocation of Submissions in the context of Peer Assessment in MOOCs. International Journal of Computer Applications. 168, 12 ( Jun 2017), 34-42. DOI=10.5120/ijca2017914507

@article{ 10.5120/ijca2017914507,
author = { M. A. Abrache, A. Qazdar, C. Cherkaoui },
title = { Involvement of Learners’ Characteristics within the Allocation of Submissions in the context of Peer Assessment in MOOCs },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2017 },
volume = { 168 },
number = { 12 },
month = { Jun },
year = { 2017 },
issn = { 0975-8887 },
pages = { 34-42 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume168/number12/27930-2017914507/ },
doi = { 10.5120/ijca2017914507 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:16:00.094234+05:30
%A M. A. Abrache
%A A. Qazdar
%A C. Cherkaoui
%T Involvement of Learners’ Characteristics within the Allocation of Submissions in the context of Peer Assessment in MOOCs
%J International Journal of Computer Applications
%@ 0975-8887
%V 168
%N 12
%P 34-42
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The contribution in the context of this paper relates to the stage of allocating submissions to the assessors within the peer assessment process in MOOCs. We propose an algorithm for the distribution of assignments that involves the learner characteristics related to the evaluation in the methodology of allocating assignments. The inputs of this algorithm are the assessment profiles of learners which include their basic characteristics linked to the evaluation process. The creation of these profiles stands on the use of an assessor model inspired from the literature on learners modeling, a model that we are also discussing in this paper.

References
  1. Siemens, G., Massive open online courses: Innovation in education. Open educational resources: Innovation, research and practice, 2013. 5.
  2. González, S.J., et al., MOOCs and Multiple Learning Styles. User-Centered Design Strategies for Massive Open Online Courses (MOOCs), 2016. 30.
  3. Suen, H.K., Peer assessment for massive open online courses (MOOCs). The International Review of Research in Open and Distributed Learning, 2014. 15(3).
  4. Yousef, A.M.F., et al. The Impact of Rubric-Based Peer Assessment on Feedback Quality in Blended MOOCs. in International Conference on Computer Supported Education. 2015. Springer.
  5. Meek, S.E., L. Blakemore, and L. Marks, Is peer review an appropriate form of assessment in a MOOC? Student participation and performance in formative peer review. Assessment & Evaluation in Higher Education, 2016: p. 1-14.
  6. Lojacono, F.G., Les MOOC: du paradigme constructiviste à celui de la reliance MOOCs: From a constructivist approach to a reliant paradigm. Revista de Lenguas para Fines Específicos, 2016. 22: p. 12-30.
  7. Dochy, F., A new assessment era: different needs, new challenges. Learning and Instruction, 2001. 10: p. 11-20.
  8. Balfour, S.P., Assessing Writing in MOOCs: Automated Essay Scoring and Calibrated Peer Review (TM). Research & Practice in Assessment, 2013. 8.
  9. Piech, C., et al., Tuned models of peer assessment in MOOCs. arXiv preprint arXiv:1307.2579, 2013.
  10. Mitros, P., et al. An integrated framework for the grading of freeform responses. in The Sixth Conference of MIT’s Learning International Networks Consortium. 2013.
  11. Kulkarni, C., et al., Peer and self assessment in massive online classes, in Design thinking research. 2015, Springer. p. 131-168.
  12. Topping, K., Peer assessment between students in colleges and universities. Review of educational Research, 1998. 68(3): p. 249-276.
  13. Topping, K.J., Peer assessment. Theory into practice, 2009. 48(1): p. 20-27.
  14. Admiraal, W., B. Huisman, and M. Van de Ven, Self-and peer assessment in massive open online courses. International Journal of Higher Education, 2014. 3(3): p. p119.
  15. Jiao, J., et al., Improving Learning in MOOCs Through Peer Feedback: How Is Learning Improved by Providing and Receiving Feedback? in Learning and Knowledge Analytics in Open Education. 2017, Springer. p. 69-87.
  16. Khalil, H. and M. Ebner. MOOCs completion rates and possible methods to improve retention-a literature review. in World Conference on Educational Multimedia, Hypermedia and Telecommunications. 2014.
  17. May, G.L. and L.E. Gueldenzoph, The effect of social style on peer evaluation ratings in project teams. Journal of Business Communication, 2006. 43(1): p. 4-20.
  18. Lin, S.S., E.Z.-F. Liu, and S.-M. Yuan, Web‐based peer assessment: feedback for students with various thinking‐styles. Journal of Computer Assisted Learning, 2001. 17(4): p. 420-432.
  19. Lan, C.-H., et al., Enrichment of peer assessment with agent negotiation. IEEE Transactions on Learning Technologies, 2011. 4(1): p. 35-46.
  20. Purchase, H.C. and J. Hamer, Peer Review in Practice: eight years of experiences with Aropä. School of Computing Science University of Glasgow 31st January 2017.
  21. Cho, K. and C.D. Schunn, Scaffolded writing and rewriting in the discipline: A web-based reciprocal peer review system. Computers & Education, 2007. 48(3): p. 409-426.
  22. Rice, W., Moodle E-Learning Course Development. 2015: Packt Publishing Ltd.
  23. Sung, Y.-T., et al., The design and application of a web-based self-and peer-assessment system. Computers & Education, 2005. 45(2): p. 187-202.
  24. Kali, Y. and M. Ronen. Design principles for online peer-evaluation: Fostering objectivity. in Proceedings of the 2005 conference on Computer support for collaborative learning: learning 2005: the next 10 years! 2005. International Society of the Learning Sciences.
  25. Paré, D.E. and S. Joordens, Peering into large lectures: examining peer and expert mark agreement using peerScholar, an online peer assessment tool. Journal of Computer Assisted Learning, 2008. 24(6): p. 526-540.
  26. Sluijsmans, D.M., et al., Peer assessment in problem based learning. Studies in educational evaluation, 2001. 27(2): p. 153-173.
  27. Honeychurch, S., et al., Peer assessment assisted by technology. International Journal of e-Assessment, 2013. 3(1).
  28. Leijen, D.A., A Novel Approach to Examine the Impact of Web-based Peer Review on the Revisions of L2 Writers. Computers and Composition, 2017. 43: p. 35-54.
  29. Xiong, Y., et al. A proposed credibility index (CI) in peer assessment. in Poster presented at the annual meeting of the National Council on Measurement in Education, Philadelphia, PA. 2014.
  30. Goldin, I.M. and K.D. Ashley. Peering inside peer review with bayesian models. in Artificial Intelligence in Education. 2011. Springer.
  31. Edx. Open Response Assessments. 2017; Available from: https://edx.readthedocs.io/projects/open-edx-building-and-running-a-course/en/named-release-birch/exercises_tools/open_response_assessments/index.html.
  32. Staubitz, T., et al. improving the peer assessment experience on MOOC platforms. in Proceedings of the Third (2016) ACM Conference on Learning@ Scale. 2016. ACM.
  33. IEEE, P1484.2/D7, 2000-11-28. Draft Standard for Learning Technology. Public and Private Information (PAPI) for Learners (PAPI Learner). Available at: http://ltsc.ieee.org/wg2/. Accessed on October 25, 2002. 2002.
  34. Oubahssi, L. and M. Grandbastien. From learner information packages to student models: Which continuum? in International Conference on Intelligent Tutoring Systems. 2006. Springer.
  35. Battou, A., Approche granulaire des objets pédagogiques en vue de l’adaptabilité dans le cadre des Environnements Informatiques pour l'Apprentissage Humain. 2012.
  36. Fini, A., The technological dimension of a massive open online course: The case of the CCK08 course tools. The International Review of Research in Open and Distributed Learning, 2009. 10(5).
  37. Brown, G.A., J. Bull, and M. Pendlebury, Assessing student learning in higher education. 2013: Routledge.
  38. Engelhard, G., Examining Rater Errors in the Assessment of Written Composition with a Many‐Faceted Rasch Model. Journal of Educational Measurement, 1994. 31(2): p. 93-112.
  39. Felder, R.M. and L.K. Silverman, Learning and teaching styles in engineering education. Engineering education, 1988. 78(7): p. 674-681.
  40. Bellifemine, F.L., G. Caire, and D. Greenwood, Developing multi-agent systems with JADE. Vol. 7. 2007: John Wiley & Sons.
Index Terms

Computer Science
Information Sciences

Keywords

Peer assessment peer review learner profile assessor model MOOC online assessment tools.

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