Needle in a haystack: Identifying learner posts that require urgent response in MOOC discussion forums

Computers and Education

Volumn 118, Issue , 2018, Pages 1-9

  Almatrafi, Omaima ^a   Johri, Aditya ^a   Rangwala, Huzefa ^a  

^a Krasnow Institute for Advanced Study   (United States)

Author keywords

Computer mediated communication; Improving classroom teaching; MOOC; Navigation

Indexed keywords

CLASSIFICATION (OF INFORMATION); CURRICULA; DATA MINING; DISTRIBUTED COMPUTER SYSTEMS; LINGUISTICS; NAVIGATION; TEACHING;

CLASSIFICATION MODELS; CLASSIFICATION TECHNIQUE; COLLABORATIVE LEARNING; COMPUTER MEDIATED COMMUNICATION; IMPROVING CLASSROOM TEACHING; LINGUISTIC FEATURES; MASSIVE OPEN ONLINE COURSE; MOOC;

EDUCATION;

EID: 85034106631     PISSN: 03601315     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compedu.2017.11.002     Document Type: Article

References (26)

1. Agrawal, A., Paepcke, A., The Stanford MOOCPosts data set. 2014 Retrieved July 10, 2017, from http://datastage.stanford.edu/StanfordMoocPosts/.
2. Agrawal, A., Venkatraman, J., Leonard, S., Paepcke, A., YouEDU: Addressing confusion in MOOC discussion forums by recommending instructional video clips. Proceedings of the 8th international conference on educational data mining, 2015, 297–304.
3. Bakharia, A., Towards cross-domain MOOC forum post classification. Proceedings of the third (2016) ACM conference on learning @ scale - L@S ′16, 2016, 253–256 http://doi.org/10.1145/2876034.2893427.
4. Chandrasekaran, M.K., Kan, M.-Y., Tan, B.C.Y., Ragupathi, K., Learning instructor intervention from MOOC Forums: Early results and issues. Proceedings of the 8th international conference on educational data mining, 2015, 218–225 Retrieved from http://arxiv.org/abs/1504.07206.
5. Chaturvedi, S., Goldwasser, D., Daumé, H., Predicting instructor's intervention in MOOC forums. 52nd annual meeting of the association for computational linguistics, ACL 2014-proceedings of the conference, Vol. 1, 2014, 1501–1511 Baltimore, Maryland, USA. Retrieved from http://www.scopus.com/inward/record.url?eid=2-s2.0-84906924486&partnerID=tZOtx3y1.
6. Cui, Y., Wise, A.F., Identifying content-related threads in MOOC discussion forums. Learning at Scale, 2015, 299–303 http://doi.org/10.1145/2724660.2728679.
7. Dringus, L.P., Ellis, T., Using data mining as a strategy for assessing asynchronous discussion forums. Computers and Education 45:1 (2005), 141–160 http://doi.org/10.1016/j.compedu.2004.05.003.
8. Hollands, F., Tirthali, D., MOOCs: Expectations and reality. 2014, Center for Benefit-Cost Studies of Education, Teachers College, Columbia University, (May) http://doi.org/10.1109/EDOC.2006.60.
9. Hone, K.S., El Said, G.R., Exploring the factors affecting MOOC retention: A survey study. Computers and Education 98 (2016), 157–168 http://doi.org/10.1016/j.compedu.2016.03.016.
10. Kim, J., Influence of group size on students' participation in online discussion forums. Computers & Education 62 (2013), 123–129 http://doi.org/10.1016/j.compedu.2012.10.025.
11. Landis, J.R., Koch, G.G., The measurement of observer agreement for categorical data. Biometrics, 33(1), 1977, 159 http://doi.org/10.2307/2529310.
12. Lin, F.R., Hsieh, L.S., Chuang, F.T., Discovering genres of online discussion threads via text mining. Computers and Education 52:2 (2009), 481–495 http://doi.org/10.1016/j.compedu.2008.10.005.
13. Liyanagunawardena, T.R., Adams, A.A., Williams, S.A., MOOCs: A systematic study of the published literature 2008-2012. International Review of Research in Open and Distance Learning 14:3 (2013), 202–227 http://doi.org/10.3329/bjms.v12i4.16658.
14. Macina, J., Srba, I., Williams, J.J., Bielikova, M., Educational question routing in online student communities. Proceedings of the eleventh ACM conference on recommender systems, 2017, ACM, Como, Italy, 47–55 http://doi.org/10.1145/3109859.3109886.
15. Maderer, J., Georgia Tech creates first online master of science in Analytics degree for less than $10,000. 2017 Retrieved April 20, 2017, from https://pe.gatech.edu/news/press-release/01072017.
16. Richardson, J.C., Koehler, A.a, Besser, E.D., Caskurlu, S., Lim, J., Mueller, C.M., Conceptualizing and investigating instructor presence in online learning environments. International Review of Research in Open & Distance Learning 16:3 (2015), 256–297 http://doi.org/10.1080/01587919.2015.1055920.
17. Shah, D., By the numbers: MOOCS in 2016. 2016 Retrieved April 20, 2017, from https://www.class-central.com/report/moocs-2015-stats/.
18. Stump, G.S., Deboer, J., Whittinghill, J., Breslow, L., Development of a framework to classify MOOC discussion forum Posts: Methodology and challenges. NIPS workshop on data driven education, (December), 2013, 1–20.
19. Wang, X., Yang, D., Wen, M., Koedinger, K., Rosé, C.P., Investigating how student's cognitive behavior in MOOC discussion forums affect learning gains. Proceedings of the 8th international conference on educational data mining, 2015, 226–233 Retrieved from http://www.educationaldatamining.org/EDM2015/proceedings/full226-233.pdf.
20. Wen, M., Yang, D., Rosé, C.P., Linguistic reflections of student engagement in massive open online courses. Proceedings of the 8th international conference on weblogs and social media ICWSM, 2014.
21. Wen, M., Yang, D., Rosé, C.P., Sentiment analysis in MOOC discussion Forums: What does it tell us?. Proceedings of the 7th international conference on educational data mining, 2014, 130–137 Retrieved from http://www.cs.cmu.edu/∼mwen/papers/edm2014-camera-ready.pdf.
22. Wise, A.F., Cui, Y., Jin, W.Q., Vytasek, J., Mining for gold: Identifying content-related MOOC discussion threads across domains through linguistic modeling. Internet and Higher Education 32 (2017), 11–28 http://doi.org/10.1016/j.iheduc.2016.08.001.
23. Wong, J.S., Pursel, B., Divinsky, A., Jansen, B.J., Analyzing MOOC discussion forum messages to identify cognitive learning information exchanges. Proceedings of the association for information science and technology, Vol. 52, 2015, 1–10 http://doi.org/10.1002/pra2.2015.145052010023.
24. Woo, Y., Reeves, T.C., Meaningful interaction in web-based learning: A social constructivist interpretation. Internet and Higher Education 10:1 (2007), 15–25 http://doi.org/10.1016/j.iheduc.2006.10.005.
25. Yang, D., Piergallini, M., Howley, I., Rose, C., Forum thread recommendation for massive open online courses. Educational Data Mining 2014 (2014), 257–260.
26. Yang, D., Wen, M., Howley, I., Kraut, R., Rose, C., Exploring the effect of confusion in discussion forums of massive open online courses. Proceedings of the second (2015) ACM conference on learning @ scale - L@S ′15, 2015, 121–130 http://doi.org/10.1145/2724660.2724677.