Table of Contents

• The LATUX workflow: designing and deploying awareness tools in technology-enabled learning settingsRoberto Martínez Maldonado, Abelardo Pardo, Negin Mirriahi, Kalina Yacef, Judy Kay, Andrew Clayphan. 1-10 [doi]
• Learning analytics beyond the LMS: the connected learning analytics toolkitKirsty Kitto, Sebastian Cross, Zak Waters, Mandy Lupton. 11-15 [doi]
• Developing an evaluation framework of quality indicators for learning analyticsMaren Scheffel, Hendrik Drachsler, Marcus Specht. 16-20 [doi]
• Exploring networks of problem-solving interactionsMichael Eagle, Andrew Hicks, Barry W. Peddycord III, Tiffany Barnes. 21-30 [doi]
• Towards better affect detectors: effect of missing skills, class features and common wrong answersYutao Wang, Neil T. Heffernan, Cristina Heffernan. 31-35 [doi]
• Exploring college major choice and middle school student behavior, affect and learning: what happens to students who game the system?Maria Ofelia Clarissa Z. San Pedro, Ryan Shaun Baker, Neil T. Heffernan, Jaclyn Ocumpaugh. 36-40 [doi]
• On the validity of peer grading and a cloud teaching assistant systemTim Vogelsang, Lara Ruppertz. 41-50 [doi]
• Examining engagement: analysing learner subpopulations in massive open online courses (MOOCs)Rebecca Ferguson, Doug Clow. 51-58 [doi]
• Socioeconomic status and MOOC enrollment: enriching demographic information with external datasetsJohn D. Hansen, Justin Reich. 59-63 [doi]
• How do you connect?: analysis of social capital accumulation in connectivist MOOCsSrecko Joksimovic, Nia Dowell, Oleksandra Skrypnyk, Vitomir Kovanovic, Dragan Gasevic, Shane Dawson, Arthur C. Graesser. 64-68 [doi]
• Learning analytics: European perspectivesRebecca Ferguson, Adam Cooper, Hendrik Drachsler, Gábor Kismihók, Anne Boyer, Kairit Tammets, Alejandra Martínez-Monés. 69-72 [doi]
• OpenCourseWare observatory: does the quality of OpenCourseWare live up to its promise?Sahar Vahdati, Christoph Lange 0002, Sören Auer. 73-82 [doi]
• Student privacy self-management: implications for learning analyticsPaul Prinsloo, Sharon Slade. 83-92 [doi]
• Who, when, and why: a machine learning approach to prioritizing students at risk of not graduating high school on timeEveraldo Aguiar, Himabindu Lakkaraju, Nasir Bhanpuri, David Miller, Ben Yuhas, Kecia L. Addison. 93-102 [doi]
• Collaborative multi-regression models for predicting students' performance in course activitiesAsmaa Elbadrawy, R. Scott Studham, George Karypis. 103-107 [doi]
• Investigating performance of students: a longitudinal studyRaheela Asif, Agathe Merceron, Mahmood Khan Pathan. 108-112 [doi]
• Using transaction-level data to diagnose knowledge gaps and misconceptionsRandall Davies, Rob Nyland, John Chapman, Gove Allen. 113-117 [doi]
• Estimation of ability from homework items when there are missing and/or multiple attemptsYoav Bergner, Kimberly F. Colvin, David E. Pritchard. 118-125 [doi]
• A time series interaction analysis method for building predictive models of learners using log dataChristopher A. Brooks, Craig Thompson, Stephanie D. Teasley. 126-135 [doi]
• Predicting success: how learners' prior knowledge, skills and activities predict MOOC performanceGregor Kennedy, Carleton Coffrin, Paula de Barba, Linda Corrin. 136-140 [doi]
• Likelihood analysis of student enrollment outcomes using learning environment variables: a case study approachScott Harrison, Renato Villano, Grace Lynch, George Chen. 141-145 [doi]
• Unsupervised modeling for understanding MOOC discussion forums: a learning analytics approachAysu Ezen-Can, Kristy Elizabeth Boyer, Shaun Kellogg, Sherry Booth. 146-150 [doi]
• Crowd-sourced learning in MOOCs: learning analytics meets measurement theorySandra Milligan. 151-155 [doi]
• What do cMOOC participants talk about in social media?: a topic analysis of discourse in a cMOOCSrecko Joksimovic, Vitomir Kovanovic, Jelena Jovanovic, Amal Zouaq, Dragan Gasevic, Marek Hatala. 156-165 [doi]
• Tracking student progress in a game-like learning environment with a Monte Carlo Bayesian knowledge tracing modelG.-H. Gweon, Hee-Sun Lee, Chad Dorsey, Robert Tinker, William Finzer, Daniel Damelin. 166-170 [doi]
• How does Bayesian knowledge tracing model emergence of knowledge about a mechanical system?Hee-Sun Lee, Gey-Hong Gweon, Chad Dorsey, Robert Tinker, William Finzer, Daniel Damelin, Nathan Kimball, Amy Pallant, Trudi Lord. 171-175 [doi]
• Learning analytics in outer space: a Hidden Naïve Bayes model for automatic student off-task behavior detectionWanli Xing, Sean P. Goggins. 176-183 [doi]
• Penetrating the black box of time-on-task estimationVitomir Kovanovic, Dragan Gasevic, Shane Dawson, Srecko Joksimovic, Ryan S. Baker, Marek Hatala. 184-193 [doi]
• You've got style: detecting writing flexibility across timeErica L. Snow, Laura K. Allen, Matthew E. Jacovina, Cecile A. Perret, Danielle S. McNamara. 194-202 [doi]
• Pssst... textual features... there is more to automatic essay scoring than just you!Scott A. Crossley, Laura K. Allen, Erica L. Snow, Danielle S. McNamara. 203-207 [doi]
• OpenEssayist: a supply and demand learning analytics tool for drafting academic essaysDenise Whitelock, Alison Twiner, John T. E. Richardson, Debora Field, Stephen G. Pulman. 208-212 [doi]
• DOP8: merging both data and analysis operators life cycles for technology enhanced learningNadine Mandran, Michael Ortega, Vanda Luengo, Denis Bouhineau. 213-217 [doi]
• A handwriting recognition system for the classroomEric Gross, Safwan Wshah, Isaiah Simmons, Gary Skinner. 218-222 [doi]
• Critical realism and learning analytics research: epistemological implications of an ontological foundationTim Rogers. 223-230 [doi]
• Topic facet modeling: semantic visual analytics for online discussion forumsI.-Han Hsiao, Piyush Awasthi. 231-235 [doi]
• Effects of sequences of socially regulated learning on group performanceInge Molenaar, Ming Ming Chiu. 236-240 [doi]
• Developing a multiple-document-processing performance assessment for epistemic literacySimon Knight, Karen Littleton. 241-245 [doi]
• Are you reading my mind?: modeling students' reading comprehension skills with natural language processing techniquesLaura K. Allen, Erica L. Snow, Danielle S. McNamara. 246-254 [doi]
• Identifying learning strategies associated with active use of video annotation softwareAbelardo Pardo, Negin Mirriahi, Shane Dawson, Yu Zhao, An Zhao, Dragan Gasevic. 255-259 [doi]
• Planning for success: how students use a grade prediction tool to win their classesCaitlin Holman, Stephen J. Aguilar, Adam Levick, Jeff Stern, Benjamin Plummer, Barry Fishman. 260-264 [doi]
• A process mining approach to linking the study of aptitude and event facets of self-regulated learningSanam Shirazi Beheshitha, Dragan Gasevic, Marek Hatala. 265-269 [doi]
• Towards data-driven mastery learningBehrooz Mostafavi, Michael Eagle, Tiffany Barnes. 270-274 [doi]
• Analysing reflective text for learning analytics: an approach using anomaly recontextualisationAndrew Gibson, Kirsty Kitto. 275-279 [doi]
• Classifying student dialogue acts with multimodal learning analyticsAysu Ezen-Can, Joseph F. Grafsgaard, James C. Lester, Kristy Elizabeth Boyer. 280-289 [doi]
• Automated detection of proactive remediation by teachers in reasoning mind classroomsWilliam L. Miller, Ryan Shaun Baker, Matthew J. Labrum, Karen Petsche, Yu-Han Liu, Angela Z. Wagner. 290-294 [doi]
• Reducing selection bias in quasi-experimental educational studiesChristopher A. Brooks, Omar Chavez, Jared Tritz, Stephanie D. Teasley. 295-299 [doi]
• Discovering clues to avoid middle school failure at early stagesManuel Ángel Jiménez-Gómez, José María Luna, Cristóbal Romero, Sebastián Ventura. 300-304 [doi]
• Combining observational and experiential data to inform the redesign of learning activitiesAbelardo Pardo, Robert A. Ellis, Rafael A. Calvo. 305-309 [doi]
• Formative and summative analyses of disciplinary engagement and learning in a big open online courseDaniel T. Hickey, Joshua D. Quick, Xinyi Shen. 310-314 [doi]
• "Scaling up" learning design: impact of learning design activities on LMS behavior and performanceBart Rienties, Lisette Toetenel, Annie Bryan. 315-319 [doi]
• An analysis of the impact of action order on future performance: the fine-grain action modelEric Van Inwegen, Seth Adjei, Yan Wang, Neil T. Heffernan. 320-324 [doi]
• Improving students' long-term retention performance: a study on personalized retention schedulesXiaolu Xiong, Yan Wang, Joseph Barbosa Beck. 325-329 [doi]
• Curriculum analysis of CS departments based on CS2013 by simplified, supervised LDATakayuki Sekiya, Yoshitatsu Matsuda, Kazunori Yamaguchi. 330-339 [doi]
• "Twitter Archeology" of learning analytics and knowledge conferencesBodong Chen, Xin Chen, Wanli Xing. 340-349 [doi]
• Discourse cohesion: a signature of collaborationMihai Dascalu, Stefan Trausan-Matu, Philippe Dessus, Danielle S. McNamara. 350-354 [doi]
• Correlations between automated rhetorical analysis and tutors' grades on student essaysDuygu Simsek, Ágnes Sándor, Simon Buckingham Shum, Rebecca Ferguson, Anna De Liddo, Denise Whitelock. 355-359 [doi]
• Leveraging multimodal learning analytics to differentiate student learning strategiesMarcelo Worsley, Paulo Blikstein. 360-367 [doi]
• From contingencies to network-level phenomena: multilevel analysis of activity and actors in heterogeneous networked learning environmentsDan Suthers. 368-377 [doi]
• Ubiquitous learning analytics in the context of real-world language learningKousuke Mouri, Hiroaki Ogata, Noriko Uosaki. 378-382 [doi]
• An exploratory study using social network analysis to model eye movements in mathematics problem solvingMengxiao Zhu, Gary Feng. 383-387 [doi]
• It's about time: 4th international workshop on temporal analyses of learning dataSimon Knight, Alyssa Friend Wise, Bodong Chen, Britte Haugan Cheng. 388-389 [doi]
• Ethical and privacy issues in the application of learning analyticsHendrik Drachsler, Tore Hoel, Maren Scheffel, Gábor Kismihók, Alan Berg, Rebecca Ferguson, Weiqin Chen, Adam Cooper, Jocelyn Manderveld. 390-391 [doi]
• 2nd int'l workshop on open badges in education (OBIE 2015): from learning evidence to learning analyticsDaniel Hickey, Jelena Jovanovic, Steve Lonn, James E. Willis. 392-393 [doi]
• VISLA: visual aspects of learning analyticsErik Duval, Katrien Verbert, Joris Klerkx, Martin Wolpers, Abelardo Pardo, Sten Govaerts, Denis Gillet, Xavier Ochoa, Denis Parra. 394-395 [doi]
• rd LAK data competitionHendrik Drachsler, Stefan Dietze, Eelco Herder, Mathieu d'Aquin, Davide Taibi, Maren Scheffel. 396-397 [doi]
• A learning analytics approach to characterize and analyze inquiry-based pedagogical processesCarlos Monroy, Virginia Snodgrass Rangel, Elizabeth R. Bell, Reid Whitaker. 398-399 [doi]
• Predicting post-training readiness to work with computers: the predominance of log-based variablesDalit Mor, Hagar Laks, Arnon Hershkovitz. 400-401 [doi]
• Investigating the impact of a notification system on student behaviors in a discourse-intensive hybrid course: a case studyZhenhua Xu, Alexandra Makos. 402-403 [doi]
• Minimum information entropy based q-matrix learning in DINA modelShiwei Ye, Yuan Sun, Haobo Wang, Yi Sun. 404-405 [doi]
• Integrated representations and small data: towards contextualized and embedded analytics tools for learnersAndreas Harrer, Tilman Göhnert. 406-407 [doi]
• Frequent sequential interactions as opportunities to engage in temporal reasoning with an online GISRaymond Kang, Josh Radinsky, Leilah Lyons. 408-409 [doi]
• The bridge report: bringing learning analytics to low-income, urban schoolsAaron Hawn. 410-411 [doi]
• Improving undergraduate student achievement in large blended courses through data-driven interventionsBernie Dodge, John Whitmer, James P. Frazee. 412-413 [doi]
• Increasing the accessibility of learning objects by automatic taggingKatja Niemann. 414-415 [doi]
• Measuring student success using predictive engineShady Shehata, Kimberly E. Arnold. 416-417 [doi]
• A learning system utilizing learners' active tracing behaviorsKazushi Maruya, Junji Watanabe, Hiroyuki Takahashi, Shoji Hashiba. 418-419 [doi]
• A case study to track teacher gestures and performance in a virtual learning environmentRoghayeh Barmaki, Charles E. Hughes. 420-421 [doi]
• Qualitatively exploring electronic portfolios: a text mining approach to measuring student emotion as an early warning indicatorFrederick Nwanganga, Everaldo Aguiar, G. Alex Ambrose, Victoria Goodrich, Nitesh V. Chawla. 422-423 [doi]
• Media multiplexity in connectivist MOOCsRafa Absar, Anatoliy A. Gruzd, Caroline Haythornthwaite, Drew Paulin. 424-425 [doi]
• Using learning analytics to study cognitive disequilibrium in a complex learning environmentMarcelo Worsley, Paulo Blikstein. 426-427 [doi]
• Analysis of learners' study logs: mouse trajectories to identify the occurrence of hesitation in solving word-reordering problemsMitsumasa Zushi, Yoshinori Miyazaki, Ken Norizuki. 428-429 [doi]
• How do students interpret feedback delivered via dashboards?Linda Corrin, Paula de Barba. 430-431 [doi]
• Learning analytics in Oz: what's happening now, what's planned, and where could it (and should it) go?Tim Rogers, Cassandra Colvin, Deborah West, Shane Dawson. 432-433 [doi]
• Text mining approach to automate teamwork assessment in group chatsAntonette Shibani, Elizabeth Koh, Helen Hong. 434-435 [doi]