Skip to main content
SpringerLink
Log in

A Software Platform for Evaluating Student Essays in Interdisciplinary Learning with Topic Classification Techniques

  • Conference paper
  • First Online:
Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky (AIED 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1831))

Included in the following conference series:

  • 2493 Accesses

Abstract

Interdisciplinary learning aims to address the growing need to solve complex problems that go beyond the boundaries of a single discipline. To better facilitate interdisciplinary learning, it is crucial to perform robust evaluations of students’ works. In this paper, we presented TopicWise, an interdisciplinary learning evaluation tool for student essays, as an initial step to address this research gap. TopicWise is developed in the context of a digital literacy course, which was part of the interdisciplinary collaborative core curriculum used in an Asian university. TopicWise reads student essays and detects the number of disciplines presented and then estimates the degree of disciplinary integration. TopicWise delivers evaluation results similar to human grader.

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 109.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 139.99
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

References

  1. Bass, L., et al.: Software Architecture in Practice. Addison-Wesley, Boston (2003)

    Google Scholar 

  2. Berasategi, N., et al.: Interdisciplinary learning at university: assessment of an interdisciplinary experience based on the case study methodology. Sustainability 12(18), 7732 (2020)

    Article  Google Scholar 

  3. Gonyea, R.M.: Self-reported data in institutional research: review and recommendations. New Direct. Inst. Res. 2005(127), 73–89 (2005)

    Google Scholar 

  4. Ivanitskaya, L., Clark, D., Montgomery, G., Primeau, R.: Interdisciplinary learning: process and outcomes. Innov. High. Educ. 27(2), 95–111 (2002)

    Article  Google Scholar 

  5. Jost, L.: Entropy and diversity. Oikos 113(2), 363–375 (2006)

    Article  Google Scholar 

  6. Klebanov, B.B., Madnani, N.: Automated evaluation of writing-50 years and counting. In: Proceedings of ACL, pp. 7796–7810 (2020)

    Google Scholar 

  7. Klein, J.T.: Evaluation of interdisciplinary and transdisciplinary research: a literature review. Am. J. Prevent. Med. 35(2), S116–S123 (2008)

    Article  Google Scholar 

  8. MacLeod, M., van der Veen, J.T.: Scaffolding interdisciplinary project-based learning: a case study. Eur. J. Eng. Educ. 45(3), 363–377 (2020)

    Article  Google Scholar 

  9. Mansilla, V.B., et al.: Targeted assessment rubric: an empirically grounded rubric for interdisciplinary writing. J. High. Educ. 80(3), 334–353 (2009)

    Article  Google Scholar 

  10. Nguyen, H.V., Litman, D.J.: Argument mining for improving the automated scoring of persuasive essays. In: Proceedings of AAAI, pp. 5892–5899. AAAI Press (2018)

    Google Scholar 

  11. Page, E.B.: The imminence of... grading essays by computer. Phi Delta Kappan 47(5), 238–243 (1966)

    Google Scholar 

  12. Persing, I., Ng, V.: Modeling thesis clarity in student essays. In: Proceedings of ACL, pp. 260–269. The Association for Computer Linguistics (2013)

    Google Scholar 

  13. Shermis, M.D., Burstein, J.: Handbook of Automated Essay Evaluation. Routledge, Abingdon (2013)

    Book  Google Scholar 

  14. Shermis, M.D., Burstein, J.C.: Automated Essay Scoring: A Cross-Disciplinary Perspective. Routledge, Abingdon (2003)

    Book  Google Scholar 

  15. Somasundaran, S., et al.: Lexical chaining for measuring discourse coherence quality in test-taker essays. In: Proceedings of COLING, pp. 950–961. ACL (2014)

    Google Scholar 

Download references

Acknowledgement

This project is supported by the Centre for Teaching, Learning and Pedagogy, Nanyang Technological University under its EdeX Programme.

Author information

Authors and Affiliations

  1. Nanyang Technological University, Singapore, Singapore

    Bryan Lim Cheng Yee, Chenyu Hou, Gaoxia Zhu, Fun Siong Lim, Shengfei Lyu & Xiuyi Fan

Authors
  1. Bryan Lim Cheng Yee
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Chenyu Hou
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Gaoxia Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Fun Siong Lim
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Shengfei Lyu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Xiuyi Fan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Xiuyi Fan .

Editor information

Editors and Affiliations

  1. University of Southern California, Los Angeles, CA, USA

    Ning Wang

  2. University of British Columbia, Vancouver, BC, Canada

    Genaro Rebolledo-Mendez

  3. University of Leeds, Leeds, UK

    Vania Dimitrova

  4. North Carolina State University, Raleigh, NC, USA

    Noboru Matsuda

  5. UNED, Madrid, Spain

    Olga C. Santos

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Yee, B.L.C., Hou, C., Zhu, G., Lim, F.S., Lyu, S., Fan, X. (2023). A Software Platform for Evaluating Student Essays in Interdisciplinary Learning with Topic Classification Techniques. In: Wang, N., Rebolledo-Mendez, G., Dimitrova, V., Matsuda, N., Santos, O.C. (eds) Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky. AIED 2023. Communications in Computer and Information Science, vol 1831. Springer, Cham. https://doi.org/10.1007/978-3-031-36336-8_100

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-36336-8_100

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-36335-1

  • Online ISBN: 978-3-031-36336-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation