Handbook of Learning Analytics

Allen, L. K., Snow, E. L., & McNamara, D. S. (2014). The long and winding road: Investigating the differential writing patterns of high and low skilled writers. In J. Stamper, Z. Pardos, M. Mavrikis, & B. M. McLaren (Eds.), Proceedings of the 7th International Conference on Educational Data Mining (EDM2014), 4–7 July, London, UK (pp. 304–307). International Educational Data Mining Society.

Allen, L. K., Snow, E. L., & McNamara, D. S. (2015). Are you reading my mind? Modeling students’ reading comprehension skills with natural language processing techniques. Proceedings of the 5th International Conference on Learning Analytics and Knowledge (LAK ʼ15), 16–20 March 2015, Poughkeepsie, NY, USA (pp. 246–254). New York: ACM. doi:10.1145/2723576.2723617

Anderson, T., & Dron, J. (2012). Learning technology through three generations of technology enhanced distance education pedagogy. European Journal of Open, Distance and E-Learning, 2012(II), 1–14.

Antonelli, F., & Sapino, M. L. (2005). A rule based approach to message board topics classification. In K. S. Candan & A. Celentano (Eds.), Advances in Multimedia Information Systems (pp. 33–48). Springer. http://link.springer.com/chapter/10.1007/11551898_6

Bateman, S., Brooks, C., McCalla, G., & Brusilovsky, P. (2007). Applying collaborative tagging to e-learning. Workshop held at the 16th International World Wide Web Conference (WWW2007), 8–12 May 2007, Banff, AB, Canada. http://www.www2007.org/workshops/paper_56.pdf

Blei, D. M. (2012). Probabilistic topic models. Communications of the ACM, 55(4), 77–84. doi:10.1145/2133806.2133826

Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent Dirichlet allocation. Journal of Machine Learning Research, 3, 993–1022.

Blikstein, P. (2011). Using learning analytics to assess students’ behavior in open-ended programming tasks. Proceedings of the 1st International Conference on Learning Analytics and Knowledge (LAK ʼ11), 27 February–1 March 2011, Banff, AB, Canada (pp. 110–116). New York: ACM. doi:10.1145/2090116.2090132

Bosnić, I., Verbert, K., & Duval, E. (2010). Automatic keywords extraction: A basis for content recommendation. Proceedings of the 4th International Workshop on Search and Exchange of e-le@rning Materials (SE@M’10), 27–28 September 2010, Barcelona, Spain (pp. 51–60). http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.204.5641&rep=rep1&type=pdf#page=54

Bramucci, R., & Gaston, J. (2012). Sherpa: Increasing student success with a recommendation engine. Proceedings of the 2nd International Conference on Learning Analytics and Knowledge (LAK ʼ12), 29 April–2 May 2012, Vancouver, BC, Canada (pp. 82–83). New York: ACM. doi:10.1145/2330601.2330625

Brooks, C., Amundson, K., & Greer, J. (2009). Detecting significant events in lecture video using supervised machine learning. Proceedings of the 2009 Conference on Artificial Intelligence in Education: Building Learning Systems That Care: From Knowledge Representation to Affective Modelling (pp. 483–490). Amsterdam, The Netherlands: IOS Press. http://dl.acm.org/citation.cfm?id=1659450.1659523

Brooks, C., Johnston, G. S., Thompson, C., & Greer, J. (2013). Detecting and categorizing indices in lecture video using supervised machine learning. In O. R. Zaïane & S. Zilles (Eds.), Advances in Artificial Intelligence (pp. 241–247). Springer. http://link.springer.com/chapter/10.1007/978-3-642-38457-8_22

Buckingham Shum, S., De Laat, M. F., De Liddo, A., Ferguson, R., Kirschner, P., Ravenscroft, A., … Whitelock, D. (2013). DCLA13: 1st International Workshop on Discourse-Centric Learning Analytics. Proceedings of the 3rd International Conference on Learning Analytics and Knowledge (LAK ’13), 8–12 April 2013, Leuven, Belgium (pp. 282–282). New York: ACM. doi:10.1145/2460296.2460357

Buckingham Shum, S., & Ferguson, R. (2012). Social learning analytics. Journal of Educational Technology & Society, 15(3), 3–26.

Buckingham Shum, S., Knight, S., McNamara, D., Allen, L., Bektik, D., & Crossley, S. (2016). Critical perspectives on writing analytics. Proceedings of the 6th International Conference on Learning Analytics & Knowledge (LAK ʼ16), 25–29 April 2016, Edinburgh, UK (pp. 481–483). New York ACM. doi:10.1145/2883851.2883854

Burrows, S., Gurevych, I., & Stein, B. (2014). The eras and trends of automatic short answer grading. International Journal of Artificial Intelligence in Education, 25(1), 60–117. doi:10.1007/s40593-014-0026-8

Calvo, R., Aditomo, A., Southavilay, V., & Yacef, K. (2012). The use of text and process mining techniques to study the impact of feedback on students’ writing processes. Proceedings of the 10th International Conference of the Learning Sciences (ICLS ʼ12), 2–6 July 2012, Sydney, Australia (pp. 416–423).

Cardinaels, K., Meire, M., & Duval, E. (2005). Automating metadata generation: The simple indexing interface. Proceedings of the 14th International Conference on World Wide Web (WWW ’05), 10–14 May 2005, Chiba, Japan (pp. 548–556). ACM. http://dl.acm.org/citation.cfm?id=1060825

Charleer, S., Santos, J. L., Klerkx, J., & Duval, E. (2014). Improving teacher awareness through activity, badge and content visualizations. In Y. Cao, T. Väljataga, J. K..T. Tang, H. Leung, M. Laanpere (Eds.), New Horizons in Web Based Learning (pp. 143–152). Springer. http://link.springer.com/chapter/10.1007/978-3-319-13296-9_16

Chatti, M. A., Dyckhoff, A. L., Schroeder, U., & Thüs, H. (2012). A reference model for learning analytics. International Journal of Technology Enhanced Learning, 4(5/6), 318–331. doi:10.1504/IJ℡.2012.051815

Chen, B. (2014). Visualizing semantic space of online discourse: The Knowledge Forum case. Proceedings of the 4th International Conference on Learning Analytics and Knowledge (LAK ʼ14), 24–28 March 2014, Indianapolis, IN, USA (pp. 271–272). New York: ACM. doi:10.1145/2567574.2567595

Chen, B., Chen, X., & Xing, W. (2015). “Twitter archeology” of Learning Analytics and Knowledge conferences. Proceedings of the 5th International Conference on Learning Analytics and Knowledge (LAK ʼ15), 16–20 March 2015, Poughkeepsie, NY, USA (pp. 340–349). New York: ACM. doi:10.1145/2723576.2723584

Chiu, M. M., & Fujita, N. (2014a). Statistical discourse analysis: A method for modeling online discussion processes. Journal of Learning Analytics, 1(3), 61–83.

Chiu, M. M., & Fujita, N. (2014b). Statistical discourse analysis of online discussions: Informal cognition, social metacognition and knowledge creation. Proceedings of the 4th International Conference on Learning Analytics and Knowledge (LAK ʼ14), 24–28 March 2014, Indianapolis, IN, USA (pp. 217–225). New York: ACM. doi:10.1145/2567574.2567580

Cohen, D. J., Troyano, J. F., Hoffman, S., Wieringa, J., Meeks, E., & Weingart, S. (Eds.). (2012). Special Issue on Topic Modeling in Digital Humanities. Journal of Digital Humanities, 2(1).

Cook, D. A., Garside, S., Levinson, A. J., Dupras, D. M., & Montori, V. M. (2010). What do we mean by web-based learning? A systematic review of the variability of interventions. Medical Education, 44(8), 765–774. doi:10.1111/j.1365-2923.2010.03723.x

Corich, S., Hunt, K., & Hunt, L. (2012). Computerised content analysis for measuring critical thinking within discussion forums. Journal of E-Learning and Knowledge Society, 2(1), 47–60.

Crossley, S., Allen, L. K., Snow, E. L., & McNamara, D. S. (2015). Pssst… Textual features… There is more to automatic essay scoring than just you! Proceedings of the 5th International Conference on Learning Analytics and Knowledge (LAK ʼ15), 16–20 March 2015, Poughkeepsie, NY, USA (pp. 203–207). New York: ACM. doi:10.1145/2723576.2723595

Crossley, S., Roscoe, R., & McNamara, D. S. (2014). What is successful writing? An investigation into the multiple ways writers can write successful essays. Written Communication, 31(2), 184–214. doi:10.1177/0741088314526354

Crossley, S., Varner, L. K., Roscoe, R. D., & McNamara, D. S. (2013). Using automated indices of cohesion to evaluate an intelligent tutoring system and an automated writing evaluation system. In H. C. Lane, K. Yacef, J. Mostow, & P. Pavlik (Eds.), Artificial Intelligence in Education (pp. 269–278). Springer. http://link.springer.com/chapter/10.1007/978-3-642-39112-5_28

Cui, Y., & Wise, A. F. (2015). Identifying content-related threads in MOOC discussion forums. Proceedings of the 2nd ACM Conference on Learning @ Scale (L@S 2015), 14–18 March 2015, Vancouver, BC, Canada (pp. 299–303). New York: ACM. doi:10.1145/2724660.2728679

De Freitas, S. (2007). Post-16 e-learning content production: A synthesis of the literature. British Journal of Educational Technology, 38(2), 349–364. doi:10.1111/j.1467-8535.2006.00632.x

De Laat, M. F., Lally, V., Lipponen, L., & Simons, R.-J. (2007). Investigating patterns of interaction in networked learning and computer-supported collaborative learning: A role for Social Network Analysis. International Journal of Computer-Supported Collaborative Learning, 2(1), 87–103. doi:10.1007/s11412-007-9006-4

De Wever, B., Schellens, T., Valcke, M., & Van Keer, H. (2006). Content analysis schemes to analyze transcripts of online asynchronous discussion groups: A review. Computers & Education, 46(1), 6–28.

Di Eugenio, B., Fossati, D., Haller, S., Yu, D., & Glass, M. (2008). Be brief, and they shall learn: Generating concise language feedback for a computer tutor. International Journal of Artificial Intelligence in Education, 18(4), 317–345.

Donnelly, R., & Gardner, J. (2011). Content analysis of computer conferencing transcripts. Interactive Learning Environments, 19(4), 303–315.

Dowell, N., Skrypnyk, O., Joksimović, S., Graesser, A. C., Dawson, S., Gašević, D., … Kovanović, V. (2015). Modeling learners’ social centrality and performance through language and discourse. In O. C. Santos, J. G. Boticario, C. Romero, M. Pechenizkiy, A. Merceron, P. Mitros, J. M. Luna, C. Mihaescu, P. Moreno, A. Hershkovitz, S. Ventura, & M. Desmarais (Eds.), Proceedings of the 8th International Conference on Education Data Mining (EDM2015), 26–29 June 2015, Madrid, Spain (pp. 250–258). International Educational Data Mining Society. http://www.educationaldatamining.org/EDM2015/uploads/papers/paper_211.pdf

Drachsler, H., Hummel, H. G. K., & Koper, R. (2008). Personal recommender systems for learners in lifelong learning networks: The requirements, techniques and model. International Journal of Learning Technology, 3(4), 404–423. doi:10.1504/IJLT.2008.019376

Dufty, D. F., Graesser, A. C., Louwerse, M., & McNamara, D. S. (2006). Assigning grade levels to textbooks: Is it just readability? In R. Sun & N. Miyake (Eds.), Proceedings of the 28th Annual Conference of the Cognitive Science Society (CogSci 2006), 26–29 July 2006, Vancouver, British Columbia, Canada (pp. 1251–1256). Austin, TX: Cognitive Science Society.

Dzikovska, M., Steinhauser, N., Farrow, E., Moore, J., & Campbell, G. (2014). BEETLE II: Deep natural language understanding and automatic feedback generation for intelligent tutoring in basic electricity and electronics. International Journal of Artificial Intelligence in Education, 24(3), 284–332. doi:10.1007/s40593-014-0017-9

Ellis, C. (2013). Broadening the scope and increasing the usefulness of learning analytics: The case for assessment analytics. British Journal of Educational Technology, 44(4), 662–664. doi:10.1111/bjet.12028

Ezen-Can, A., Boyer, K. E., Kellogg, S., & Booth, S. (2015). Unsupervised modeling for understanding MOOC discussion forums: A learning analytics approach. Proceedings of the 5th International Conference on Learning Analytics and Knowledge (LAK ʼ15), 16–20 March 2015, Poughkeepsie, NY, USA (pp. 146–150). New York: ACM. doi:10.1145/2723576.2723589

Ferguson, R. (2012). Learning analytics: Drivers, developments and challenges. International Journal of Technology Enhanced Learning, 4(5/6), 304. doi:10.1504/IJTEL.2012.051816

Ferguson, R., & Buckingham Shum, S. (2012). Social learning analytics: Five approaches. Proceedings of the 2nd International Conference on Learning Analytics and Knowledge (LAK ʼ12), 29 April–2 May 2012, Vancouver, BC, Canada (pp. 23–33). New York: ACM. doi:10.1145/2330601.2330616

Foltz, P. W., Laham, D., Landauer, T. K., Foltz, P. W., Laham, D., & Landauer, T. K. (1999). Automated essay scoring: Applications to educational technology. In B. Collis & R. Oliver (Eds.), Proceedings of EdMedia: World Conference on Educational Media and Technology 1999, 19–24 June 1999, Seattle, WA, USA (pp. 939–944). Association for the Advancement of Computing in Education (AACE). https://www.learntechlib.org/p/6607

Foltz, P. W., & Rosenstein, M. (2015). Analysis of a large-scale formative writing assessment system with automated feedback. Proceedings of the 2nd ACM Conference on Learning @ Scale (L@S 2015), 14–18 March 2015, Vancouver, BC, Canada (pp. 339–342). New York: ACM. doi:10.1145/2724660.2728688

Garrison, D. R., Anderson, T., & Archer, W. (2001). Critical thinking, cognitive presence, and computer conferencing in distance education. American Journal of Distance Education, 15(1), 7–23.

Gašević, D., Dawson, S., & Siemens, G. (2015). Let’s not forget: Learning analytics are about learning. TechTrends, 59(1), 64–71. doi:10.1007/s11528-014-0822-x

Gašević, D., Mirriahi, N., & Dawson, S. (2014). Analytics of the effects of video use and instruction to support reflective learning. Proceedings of the 4th International Conference on Learning Analytics and Knowledge (LAK ʼ14), 24–28 March 2014, Indianapolis, IN, USA (pp. 123–132). New York: ACM. doi:10.1145/2567574.2567590

Graesser, A. C., McNamara, D. S., & Kulikowich, J. M. (2011). Coh-Metrix: Providing multilevel analyses of text characteristics. Educational Researcher, 40(5), 223–234. doi:10.3102/0013189X11413260

Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81–112. doi:10.3102/003465430298487

Hecking, T., & Hoppe, H. U. (2015). A network based approach for the visualization and analysis of collaboratively edited texts. Proceedings of the Workshop on Visual Aspects of Learning Analytics (VISLA ʼ15), 16–20 March 2015, Poughkeepsie, NY, USA (pp. XXX–XXX). http://ceur-ws.org/Vol-1518/paper4.pdf

Hever, R., De Groot, R., De Laat, M., Harrer, A., Hoppe, U., McLaren, B. M., & Scheuer, O. (2007). Combining structural, process-oriented and textual elements to generate awareness indicators for graphical e-discussions. In C. Chinn, G. Erkens, & S. Puntambekar (Eds.), Proceedings of the 7th International Conference on Computer-Supported Collaborative Learning (CSCL 2007), 16–21 July 2007, New Brunswick, NJ, USA (pp. 289–291). International Society of the Learning Sciences. http://dl.acm.org/citation.cfm?id=1599600.1599654

Hong, L., & Davison, B. D. (2010). Empirical study of topic modeling in Twitter. Proceedings of the 1st Workshop on Social Media Analytics (SOMA ’10), 25–28 July 2010, Washington, DC, USA (pp. 80–88). New York: ACM. doi:10.1145/1964858.1964870

Hosseini, R., & Brusilovsky, P. (2014). Example-based problem solving support using concept analysis of programming content. In S. Trausan-Matu, K. E. Boyer, M. Crosby, & K. Panourgia (Eds.), Intelligent Tutoring Systems (pp. 683–685). Springer. http://link.springer.com/chapter/10.1007/978-3-319-07221-0_106

Hsiao, I.-H., & Awasthi, P. (2015). Topic facet modeling: Semantic visual analytics for online discussion forums. Proceedings of the 5th International Conference on Learning Analytics and Knowledge (LAK ʼ15), 16–20 March 2015, Poughkeepsie, NY, USA (pp. 231–235). New York: ACM. doi:10.1145/2723576.2723613

Joksimović, S., Dowell, N., Skrypnyk, O., Kovanović, V., Gašević, D., Dawson, S., & Graesser, A. C. (2015). Exploring the accumulation of social capital in cMOOC through language and discourse. Under Review.

Joksimović, S., Gašević, D., Kovanović, V., Adesope, O., & Hatala, M. (2014). Psychological characteristics in cognitive presence of communities of inquiry: A linguistic analysis of online discussions. The Internet and Higher Education, 22, 1–10.

Joksimović, S., Kovanović, V., Jovanović, J., Zouaq, A., Gašević, D., & Hatala, M. (2015). What do cMOOC participants talk about in social media? A topic analysis of discourse in a cMOOC. Proceedings of the 5th International Conference on Learning Analytics and Knowledge (LAK ʼ15), 16–20 March 2015, Poughkeepsie, NY, USA (pp. 156–165). New York: ACM.

Knight, S., & Littleton, K. (2015). Discourse centric learning analytics: Mapping the terrain. Journal of Learning Analytics, 2(1), 185–209.

Kovanović, V., Joksimović, S., Gašević, D., & Hatala, M. (2014). Automated content analysis of online discussion transcripts. In K. Yacef & H. Drachsler (Eds.), Proceedings of the Workshops at the LAK 2014 Conference (LAK-WS 2014), 24–28 March 2014, IN, Indiana, USA. http://ceur-ws.org/Vol-1137/LA_machinelearning_submission_1.pdf

Kovanović, V., Joksimović, S., Waters, Z., Gašević, D., Kitto, K., Hatala, M., & Siemens, G. (2016). Towards automated content analysis of discussion transcripts: A cognitive presence case. Proceedings of the 6th International Conference on Learning Analytics & Knowledge (LAK ʼ16), 25–29 April 2016, Edinburgh, UK (pp. 15–24). New York: ACM. doi:10.1145/2883851.2883950

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