Skip to main content
SpringerLink
Log in

Design and Implementation of Dashboards to Support Teachers Decision-Making Process in e-Assessment Systems

  • Chapter
  • First Online:
Engineering Data-Driven Adaptive Trust-based e-Assessment Systems

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 34))

Abstract

The growing number of universities adopting some form of e-learning in recent years has raised some concerns about how to ensure students’ authentication, and the authorship of the assessment activities they deliver. There are several strategies and market tools that can help teachers in these tasks. While the usage of plagiarism detection tools for checking authorship is common practice (above all in fully online universities), the use of biometric instruments for ensuring students’ identity is less extended. Although all these tools collect a large amount and variety of data, there is a lack of software systems that can integrate such data, and show the information that may be extracted from these data in a visual and meaningful way that fits the teachers’ needs. Precisely, the objective of this chapter is to present a set of dashboards that integrate data collected by different kinds of authentication and authorship instruments, oriented to assist the decision-making process of teachers, above all in case of suspicion of students’ dishonest academic behavior. Although these dashboards have been designed and implemented in the context of TeSLA project, the experience and conclusions provided here are of interest to researchers and practitioners aiming to develop dashboards with learning analytics purposes at higher education. For this reason, this chapter also provides a discussion and review of the most prominent analytical efforts in universities.

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 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight 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

Notes

  1. 1.

    https://moodle.org/.

  2. 2.

    https://www.blackboard.com/index.html.

  3. 3.

    https://www.urkund.com/about-urkund.

Abbreviations

API:

Application Programming Interface

ICT:

Information and Communication Technologies

KPI:

Key Performance Indicators

LMS:

Learning Management System

MOOC:

Massive Open Online Courses

References

  1. Ali AMET, Abdulla HMD, Snasel V (2011) Overview and comparison of plagiarism detection tools. In: DATESO pp 161–172

    Google Scholar 

  2. Ali L, Asadi M, Gaševic D, Jovanovic J, Hatala M (2013) Factors influencing beliefs for adoption of a learning analytics tool: an empirical study. Comput Educ 62:130–148

    Article  Google Scholar 

  3. Arnold KE, Pistilli MD (2012) Course signals at Purdue: using learning analytics to increase student success. In: Proceedings of the 2nd international conference on learning analytics and knowledge. ACM, pp 267–270

    Google Scholar 

  4. Baneres D, Rodriguez-Gonzalez ME, Serra M (2019) An early feedback prediction system for learners at-risk within a first-year higher education course. IEEE Trans Learn Technol

    Google Scholar 

  5. Baranovic M, Madunic M, Mekterovic I (2003) Data warehouse as a part of the higher education information system in Croatia. In: Proceedings of the 25th international conference on information technology interfaces, 2003. ITI 2003. IEEE, pp 121–126

    Google Scholar 

  6. Campbell JP, DeBlois PB, Oblinger DG (2007) Academic analytics: a new tool for a new era. Educause Rev 42(4):40

    Google Scholar 

  7. Chatti MA, Dyckhoff AL, Schroeder U, Thüs H (2013) A reference model for learning analytics. Int J Technol Enhanced Learn 4(5–6):318–331

    Google Scholar 

  8. Chertok IRA, Barnes ER, Gilleland D (2014) Academic integrity in the online learning environment for health sciences students. Nurse Educ Today 34(10):1324–1329

    Article  Google Scholar 

  9. Davenport T, Harris J (2017) Competing on analytics: updated, with a new introduction: the new science of winning. Harvard Business Press

    Google Scholar 

  10. Di Tria F, Lefons E, Tangorra F (2012) Research data mart in an academic system. In: 2012 spring congress on engineering and technology. IEEE, pp 1–5

    Google Scholar 

  11. Doerfel ML, Ruben BD (2002) Developing more adaptive, innovative, and interactive organizations. New Dir High Educ 2002(118):5–28

    Article  Google Scholar 

  12. Elias T (2011) Learning analytics. Learning, 1–22

    Google Scholar 

  13. Eckerson WW (2010) Performance dashboards: measuring, monitoring, and managing your business. Wiley, New York

    Google Scholar 

  14. Eckerson W, Hammond M (2011) Visual reporting and analysis, TDWI best practices report. TDWI, Chatsworth

    Google Scholar 

  15. Ferguson R (2012) Learning analytics: drivers, developments and challenges. Int J Technol Enhanced Learn 4(5/6):304–317

    Article  Google Scholar 

  16. Few S (2006) Information dashboard design. O’Reilly

    Google Scholar 

  17. Gašević D, Dawson S, Siemens G (2015) Let’s not forget: learning analytics are about learning. TechTrends 59(1):64–71

    Article  Google Scholar 

  18. Glendinning I (2014) Responses to student plagiarism in higher education across Europe. Int J Educ Integrity 10(1)

    Google Scholar 

  19. Glover RH (1986) Designing a decision-support system for enrollment management. Res High Educ 24(1):15–34

    Article  Google Scholar 

  20. Glover RH (1993) Developing executive information systems for higher education: new directions for institutional research, vol 77. Jossey-Bass

    Google Scholar 

  21. Govaerts S, Verbert K, Duval E, Pardo A (2012) The student activity meter for awareness and self-reflection. In: CHI’12 extended abstracts on human factors in computing systems. ACM, pp 869–884

    Google Scholar 

  22. Green J, Rutherford S, Turner T (2009) Best practice in using business intelligence to determine research strategy. Perspectives 13(2):48–55

    Google Scholar 

  23. Guitart I, Conesa J (2015) Analytic information systems in the context of higher education: expectations, reality and trends. In: 2015 international conference on intelligent networking and collaborative systems. IEEE, pp 294–300

    Google Scholar 

  24. Guitart I, Conesa J (2016) Creating university analytical information systems: a grand challenge for information systems research. In: Formative assessment, learning data analytics and gamification. Academic Press, pp 167–186

    Google Scholar 

  25. Guitart I, Conesa J, Casas J (2016) A preliminary study about the analytic maturity of educational organizations. In: 2016 international conference on intelligent networking and collaborative systems (INCoS). IEEE, pp 345–350

    Google Scholar 

  26. Ida M (2014) Structure of university database system and data analysis. In: 16th international conference on advanced communication technology. IEEE, pp 553–557

    Google Scholar 

  27. Kim J, Jo IH, Park Y (2016) Effects of learning analytics dashboard: analyzing the relations among dashboard utilization, satisfaction, and learning achievement. Asia Pac Educ Rev 17(1):13–24

    Article  Google Scholar 

  28. Kitto K, Bakharia A, Lupton M, Mallet D, Banks J, Bruza P, Siemens G (2016) The connected learning analytics toolkit. In: Proceedings of the sixth international conference on learning analytics & knowledge. ACM, pp 548–549

    Google Scholar 

  29. Kleesuwan S, Mitatha S, Yupapin PP, Piyatamrong B (2010) Business intelligence in Thailand’s higher educational resources management. Procedia-Soc Behav Sci 2(1):84–87

    Article  Google Scholar 

  30. Leony D, Pardo A, de la Fuente Valentín L, de Castro DS, Kloos CD (2012) GLASS: a learning analytics visualization tool. In: Proceedings of the 2nd international conference on learning analytics and knowledge. ACM, pp 162–163

    Google Scholar 

  31. Macfadyen LP, Dawson S (2012) Numbers are not enough. Why e-learning analytics failed to inform an institutional strategic plan. J Educ Technol Soc 15(3):149–163

    Google Scholar 

  32. Maniu I, Maniu GC (2015) Data analysis techniques for examining factors influencing student’s enrollment decision. SEA-Pract Appl Sci 3(2):61–64

    Google Scholar 

  33. Minguillón J, Conesa J, Rodríguez ME, Santanach F (2018) Learning analytics in practice: providing E-learning researchers and practitioners with activity data. In: Frontiers of cyberlearning. Springer, Singapore, pp 145–167

    Google Scholar 

  34. Mitchell JJ, Ryder AJ (2013) Developing and using dashboard indicators in student affairs assessment. New Dir Stud Serv 2013(142):71–81

    Google Scholar 

  35. Moore LJ, Greenwood AG (1984) Decision support systems for academic administration. AIR Professional File

    Google Scholar 

  36. Mohd WMBW, Embong A, Zain JM (2008) A knowledge-based digital dashboard for higher learning institutions. In: Joint European conference on machine learning and knowledge discovery in databases. Springer, Berlin, Heidelberg, pp 684–689

    Google Scholar 

  37. Muntean M, Bologa A, Bologa R, Florea A (2011) Business intelligence systems in support of university strategy. Recent Res Educ Technol, 118–123

    Google Scholar 

  38. Park C (2003) In other (people’s) words: Plagiarism by university students–literature and lessons. Assess Eval High Educ 28(5):471–488

    Article  Google Scholar 

  39. Park Y, Jo IH (2015) Development of the learning analytics dashboard to support students’ learning performance. J Univ Comput Sci 21(1):110

    Google Scholar 

  40. Piedade MB, Santos MY (2010) Business intelligence in higher education: enhancing the teaching-learning process with a SRM system. In: 5th Iberian conference on information systems and technologies. IEEE, pp 1–5

    Google Scholar 

  41. Rice A, Abshire D, Christakis M, Sherman G (2010) The assessment movement toward key performance indicators. In: Meeting of NASPA international assessment and retention conference, Baltimore, Md

    Google Scholar 

  42. Roberts LD, Howell JA, Seaman K (2017) Give me a customizable dashboard: personalized learning analytics dashboards in higher education. Technol Knowl Learn 22(3):317–333

    Article  Google Scholar 

  43. Rodríguez ME, Baneres D, Ivanova M, Durcheva M (2017) Case study analysis on blended and online institutions by using a trustworthy system. In: International conference on technology enhanced assessment. Springer, Cham, pp 40–53

    Chapter  Google Scholar 

  44. Schwendimann BA, Rodriguez-Triana MJ, Vozniuk A, Prieto LP, Boroujeni MS, Holzer A, Dillenbourg P (2017) Perceiving learning at a glance: a systematic literature review of learning dashboard research. IEEE Trans Learn Technol 10(1):30–41

    Article  Google Scholar 

  45. Siemens G, Long P (2011) Penetrating the fog: analytics in learning and education. Educause Rev 46(5):30

    Google Scholar 

  46. Siemens G, d Baker RS (2012) Learning analytics and educational data mining: towards communication and collaboration. In: Proceedings of the 2nd international conference on learning analytics and knowledge. ACM, pp 252–254

    Google Scholar 

  47. Siemens G, Dawson S, Lynch G (2013) Improving the quality and productivity of the higher education sector. Policy and strategy for systems-level deployment of learning analytics. Society for Learning Analytics Research for the Australian Office for Learning and Teaching, Canberra, Australia

    Google Scholar 

  48. Stocker R (2012) The role of business intelligence dashboards in higher education. Credit Control 33(1):37–42

    Google Scholar 

  49. Turban E, Cameron Fisher J, Altman S (1988) Decision support systems in academic administration. J Educ Adm 26(1):97–113

    Article  Google Scholar 

  50. Van Barneveld A, Arnold KE, Campbell JP (2012) Analytics in higher education: establishing a common language. EDUCAUSE Learn Initiative 1(1):l–ll

    Google Scholar 

  51. Verbert K, Duval E, Klerkx J, Govaerts S, Santos JL (2013) Learning analytics dashboard applications. Am Behav Sci 57(10):1500–1509

    Article  Google Scholar 

  52. West DM (2012) Big data for education: Data mining, data analytics, and web dashboards. Gov Stud Brookings 4(1)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Universitat Oberta de Catalunya, Rambla del Poblenou, 156, 08018, Barcelona, Spain

    Isabel Guitart Hormigo, M. Elena Rodríguez & Xavier Baró

Authors
  1. Isabel Guitart Hormigo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M. Elena Rodríguez
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xavier Baró
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Isabel Guitart Hormigo .

Editor information

Editors and Affiliations

  1. Faculty of Computer Science, Multimedia and Telecommunications, Universitat Oberta de Catalunya, Barcelona, Spain

    David Baneres

  2. Faculty of Computer Science, Multimedia and Telecommunications, Universitat Oberta de Catalunya, Barcelona, Spain

    M. Elena Rodríguez

  3. Faculty of Computer Science, Multimedia and Telecommunications, Universitat Oberta de Catalunya, Barcelona, Spain

    Ana Elena Guerrero-Roldán

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Guitart Hormigo, I., Rodríguez, M.E., Baró, X. (2020). Design and Implementation of Dashboards to Support Teachers Decision-Making Process in e-Assessment Systems. In: Baneres, D., Rodríguez, M., Guerrero-Roldán, A. (eds) Engineering Data-Driven Adaptive Trust-based e-Assessment Systems. Lecture Notes on Data Engineering and Communications Technologies, vol 34. Springer, Cham. https://doi.org/10.1007/978-3-030-29326-0_6

Download citation

Publish with us

Policies and ethics

Search

Navigation