Table of Contents

• Analyzing the consistency in within-activity learning patterns in blended learningVarshita Sher, Marek Hatala, Dragan Gasevic. 1-10 [doi]
• Evaluating teachers' perceptions of students' questions organizationFatima Harrak, François Bouchet, Vanda Luengo, Pierre Gillois. 11-16 [doi]
• Predicting student success in a blended learning environmentSteven Van Goidsenhoven, Daria Bogdanova, Galina Deeva, Seppe Vanden Broucke, Jochen De Weerdt, Monique Snoeck. 17-25 [doi]
• Comparing teachers' use of mirroring and advising dashboardsAnouschka van Leeuwen, Nikol Rummel. 26-34 [doi]
• Learning analytics dashboards: the past, the present and the futureKatrien Verbert, Xavier Ochoa, Robin De Croon, Raphael A. Dourado, Tinne De Laet. 35-40 [doi]
• Automated insightful drill-down recommendations for learning analytics dashboardsShiva Shabaninejad, Hassan Khosravi, Marta Indulska, Aneesha Bakharia, Pedro T. Isaías. 41-46 [doi]
• Trace data from student solutions to genetics problems reveals variance in the processes related to different course outcomesMelanie Peffer, David Quigley, Liza Brusman, Jennifer Avena, Jennifer Knight. 47-52 [doi]
• How working memory capacity limits success in self-directed learning: a cognitive model of search and concept formationPaul Seitlinger, Abida Bibi, Õnne Uus, Tobias Ley. 53-62 [doi]
• LA-DECK: a card-based learning analytics co-design toolCarlos Gerardo Prieto-Alvarez, Roberto Martínez Maldonado, Simon Buckingham Shum. 63-72 [doi]
• Inspiration cards workshops with primary teachers in the early co-design stages of learning analyticsYvonne Vezzoli, Manolis Mavrikis, Asimina Vasalou. 73-82 [doi]
• Fostering and supporting empirical research on evaluative judgement via a crowdsourced adaptive learning systemHassan Khosravi, George Gyamii, Barbara E. Hanna, Jason Lodge. 83-88 [doi]
• Smart dictionary for e-book reading analyticsLouis Lecailliez, Brendan Flanagan, Mei-Rong Alice Chen, Hiroaki Ogata. 89-93 [doi]
• Involving teachers in learning analytics design: lessons learned from two case studiesKonstantinos Michos, Charles Lang, Davinia Hernández Leo, Detra Price-Dennis. 94-99 [doi]
• Learning-centred translucence: an approach to understand how teachers talk about classroom dataRita Prestigiacomo, Roger Hadgraft, Jane Hunter, Lori Locker, Simon Knight 0001, Elise van den Hoven, Roberto Martínez Maldonado. 100-105 [doi]
• Exploring student approaches to learning through sequence analysis of reading logsGökhan Akçapinar, Mei-Rong Alice Chen, Rwitajit Majumdar, Brendan Flanagan, Hiroaki Ogata. 106-111 [doi]
• Slow is good: the effect of diligence on student performance in the case of an adaptive learning system for health literacyLeon Fadljevic, Katharina Maitz, Dominik Kowald, Viktoria Pammer-Schindler, Barbara Gasteiger-Klicpera. 112-117 [doi]
• Decoding the performance in an out-of-context problem during blocked practiceSweety Agrawal, Amar Lalwani. 118-123 [doi]
• Exploring exam strategies of successful first year engineering studentsJakub Kuzilek, Zdenek Zdráhal, Jonas Vaclavek, Viktor Fuglik, Jan Skocilas. 124-128 [doi]
• Dialogue attributes that inform depth and quality of participation in course discussion forumsElaine Farrow, Johanna D. Moore, Dragan Gasevic. 129-134 [doi]
• Towards automated analysis of cognitive presence in MOOC discussions: a manual classification studyYuanyuan Hu, Claire Donald, Nasser Giacaman, Zexuan Zhu. 135-140 [doi]
• Towards automatic content analysis of social presence in transcripts of online discussionsMaverick Andre Dionisio Ferreira, Vitor Rolim, Rafael Ferreira Mello, Rafael Dueire Lins, Guanliang Chen, Dragan Gasevic. 141-150 [doi]
• Analytics of learning strategies: the association with the personality traitsWannisa Matcha, Dragan Gasevic, Jelena Jovanovic, Nora'Ayu Ahmad Uzir, Chris W. Oliver, Andrew Murray, Danijela Gasevic. 151-160 [doi]
• Supporting actionable intelligence: reframing the analysis of observed study strategiesJelena Jovanovic, Shane Dawson, Srecko Joksimovic, George Siemens. 161-170 [doi]
• Towards skills-based curriculum analytics: can we automate the recognition of prior learning?Kirsty Kitto, Nikhil Sarathy, Aleksandr Gromov, Ming Liu, Katarzyna Musial, Simon Buckingham Shum. 171-180 [doi]
• Design of a curriculum analytics tool to support continuous improvement processes in higher educationIsabel Hilliger, Camila Aguirre, Constanza Miranda, Sergio Celis, Mar Pérez-Sanagustín. 181-186 [doi]
• Intergroup and interpersonal forum positioning in shared-thread and post-reply networksOleksandra Poquet, Jelena Jovanovic. 187-196 [doi]
• Towards understanding the lifespan and spread of ideas: epidemiological modeling of participation on TwitterSai Santosh Sasank Peri, Bodong Chen, Angela Liegey Dougall, George Siemens. 197-202 [doi]
• Socio-temporal dynamics in peer interaction eventsBodong Chen, Oleksandra Poquet. 203-208 [doi]
• An exploratory approach to measuring collaborative engagement in child robot interactionYanghee Kim, Sachit Butail, Michael Tscholl, Lichuan Liu, Yunlong Wang. 209-217 [doi]
• The SEIRA approach: course embedded activities to promote academic integrity and literacies in first year engineeringAndrea Duff, Andrew Zamecnik, Abelardo Pardo, Elizabeth Smith. 218-223 [doi]
• Learning with background music: a field experimentFanjie Li, Xiao Hu 0001, Ying Que. 224-229 [doi]
• The privacy paradox and its implications for learning analyticsYi-Shan Tsai, Alexander Whitelock-Wainwright, Dragan Gasevic. 230-239 [doi]
• Perceptions and expectations about learning analytics from a brazilian higher education institutionTaciana Pontual Falcão, Rafael Ferreira Mello, Rodrigo Lins Rodrigues, Juliana Regueira Basto Diniz, Yi-Shan Tsai, Dragan Gasevic. 240-249 [doi]
• Exploring the usage of thermal imaging for understanding video lecture designs and students' experiencesNamrata Srivastava, Sadia Nawaz, Jason M. Lodge, Eduardo Velloso, Sarah M. Erfani, James Bailey 0001. 250-259 [doi]
• Is faster better?: a study of video playback speedDavid Lang, Guanling Chen, Kathy Mirzaei, Andreas Paepcke. 260-269 [doi]
• Modelling collaborative problem-solving competence with transparent learning analytics: is video data enough?Mutlu Cukurova, Qi Zhou, Daniel Spikol, Lorenzo Landolfi. 270-275 [doi]
• The relationship between confusion and metacognitive strategies in Betty's BrainYingbin Zhang, Luc Paquette, Ryan S. Baker, Jaclyn Ocumpaugh, Nigel Bosch, Anabil Munshi, Gautam Biswas. 276-284 [doi]
• A bayesian model of individual differences and flexibility in inductive reasoning for categorization of examplesLouis Faucon, Jennifer K. Olsen, Pierre Dillenbourg. 285-294 [doi]
• Focused or stuck together: multimodal patterns reveal triads' performance in collaborative problem solvingHana Vrzakova, Mary Jean Amon, Angela Stewart, Nicholas D. Duran, Sidney K. D'Mello. 295-304 [doi]
• iSENS: an integrated approach to combining epistemic and social network analysesZachari Swiecki, David Williamson Shaffer. 305-313 [doi]
• High resolution temporal network analysis to understand and improve collaborative learningMohammed Saqr, Jalal Nouri. 314-319 [doi]
• Learning to represent healthcare providers knowledge of neonatal emergency care: findings from a smartphone-based learning intervention targeting clinicians from LMICsTimothy Tuti, Chris Paton, Niall Winters. 320-329 [doi]
• Personalized visualizations to promote young learners' SRL: the learning path appInge Molenaar, Anne Horvers, Rick Dijkstra, Ryan S. Baker. 330-339 [doi]
• How patterns of students dashboard use are related to their achievement and self-regulatory engagementFatemeh Salehian Kia, Stephanie D. Teasley, Marek Hatala, Stuart A. Karabenick, Matthew Kay. 340-349 [doi]
• Designing for serendipity in a university course recommendation systemZachary A. Pardos, Weijie Jiang. 350-359 [doi]
• Complementing educational recommender systems with open learner modelsSolmaz Abdi, Hassan Khosravi, Shazia W. Sadiq, Dragan Gasevic. 360-365 [doi]
• Are forum networks social networks?: a methodological perspectiveOleksandra Poquet, Liubov Tupikina, Marc Santolini. 366-375 [doi]
• Rethinking time-on-task estimation with outlier detection accounting for individual, time, and task differencesQuan Nguyen. 376-381 [doi]
• Prediction of students' assessment readiness in online learning environments: the sequence mattersDonia Malekian, James Bailey 0001, Gregor E. Kennedy. 382-391 [doi]
• Analytics of time management and learning strategies for effective online learning in blended environmentsNora'Ayu Ahmad Uzir, Dragan Gasevic, Jelena Jovanovic, Wannisa Matcha, Lisa-Angelique Lim, Anthea Fudge. 392-401 [doi]
• Combining analytic methods to unlock sequential and temporal patterns of self-regulated learningJohn Saint, Dragan Gasevic, Wannisa Matcha, Nora'Ayu Ahmad Uzir, Abelardo Pardo. 402-411 [doi]
• R2DE: a NLP approach to estimating IRT parameters of newly generated questionsLuca Benedetto, Andrea Cappelli, Roberto Turrin, Paolo Cremonesi. 412-421 [doi]
• Applying prerequisite structure inference to adaptive testingSam Saarinen, Evan Cater, Michael L. Littman. 422-427 [doi]
• How good is my feedback?: a content analysis of written feedbackAnderson Pinheiro Cavalcanti, Arthur Diego, Rafael Ferreira Mello, Katerina Mangaroska, André Nascimento, Fred Freitas, Dragan Gasevic. 428-437 [doi]
• Understanding students' engagement with personalised feedback messagesHamideh Iraj, Anthea Fudge, Margaret Faulkner, Abelardo Pardo, Vitomir Kovanovic. 438-447 [doi]
• Characterizing and influencing students' tendency to write self-explanations in online homeworkYuya Asano, Jaemarie Solyst, Joseph Jay Williams. 448-453 [doi]
• Testing the reliability of inter-rater reliabilityBrendan R. Eagan, Jais Brohinsky, Jingyi Wang, David Williamson Shaffer. 454-461 [doi]
• Constructing and predicting school advice for academic achievement: a comparison of item response theory and machine learning techniquesKoen Niemeijer, Remco Feskens, Georg Krempl, Jesse Koops, Matthieu J. S. Brinkhuis. 462-471 [doi]
• Exploration of the robustness and generalizability of the additive factors modelTomás Effenberger, Radek Pelánek, Jaroslav Cechák. 472-479 [doi]
• Predicting learners' effortful behaviour in adaptive assessment using multimodal dataKshitij Sharma, Zacharoula K. Papamitsiou, Jennifer K. Olsen, Michail N. Giannakos. 480-489 [doi]
• Detecting learning in noisy data: the case of oral reading fluencyBeata Beigman Klebanov, Anastassia Loukina, John Lockwood, Van Rynald T. Liceralde, John Sabatini, Nitin Madnani, Binod Gyawali, Zuowei Wang, Jennifer Lentini. 490-495 [doi]
• Using a cluster-based regime-switching dynamic model to understand embodied mathematical learningLu Ou, Alejandro Andrade, Rosa Alberto, Gitte van Helden, Arthur Bakker. 496-501 [doi]
• edX log data analysis made easy: introducing ELAT: An open-source, privacy-aware and browser-based edX log data analysis toolManuel Valle Torre, Esther Tan, Claudia Hauff. 502-511 [doi]
• Assessment that matters: balancing reliability and learner-centered pedagogy in MOOC assessmentGiora Alexandron, Mary Ellen Wiltrout, Aviram Berg, José A. Ruipérez Valiente. 512-517 [doi]
• Macro MOOC learning analytics: exploring trends across global and regional providersJosé A. Ruipérez Valiente, Matt Jenner, Thomas Staubitz, Xitong Li, Tobias Rohloff, Sherif A. Halawa, Carlos Turro, Yuan Cheng, Jiayin Zhang, Ignacio M. Despujol, Justin Reich. 518-523 [doi]
• Self-regulated learning and learning analytics in online learning environments: a review of empirical researchOlga Viberg, Mohammad Khalil, Martine Baars. 524-533 [doi]
• What college students say, and what they do: aligning self-regulated learning theory with behavioral logsJoshua Quick, Benjamin Motz, Jamie Israel, Jason Kaetzel. 534-543 [doi]
• Let's shine together!: a comparative study between learning analytics and educational data miningGuanliang Chen, Vitor Rolim, Rafael Ferreira Mello, Dragan Gasevic. 544-553 [doi]
• Learning analytics challenges: trade-offs, methodology, scalabilityRadek Pelánek. 554-558 [doi]
• From childhood to maturity: Are we there yet? Mapping the intellectual progress in learning analytics during the past decadeZacharoula K. Papamitsiou, Michail N. Giannakos, Xavier Ochoa. 559-568 [doi]
• From theory to action: developing and evaluating learning analytics for learning designKorah J. Wiley, Yannis Dimitriadis 0001, Allison Bradford, Marcia C. Linn. 569-578 [doi]
• Disciplinary differences in blended learning design: a network analytic studyAlexander Whitelock-Wainwright, Yi-Shan Tsai, Kayley Lyons, Svetlana Kaliff, Mike Bryant, Kris Ryan, Dragan Gasevic. 579-588 [doi]
• #Confused and beyond: detecting confusion in course forums using students' hashtagsShay A. Geller, Nicholas Hoernle, Kobi Gal, Avi Segal, Amy X. Zhang, David R. Karger, Marc T. Facciotti, Michele Igo. 589-594 [doi]
• How and how well do students reflect?: multi-dimensional automated reflection assessment in health professions educationYeonji Jung, Alyssa Friend Wise. 595-604 [doi]
• Towards automatic cross-language classification of cognitive presence in online discussionsGian Barbosa, Raissa Camelo, Anderson Pinheiro Cavalcanti, Péricles Miranda, Rafael Ferreira Mello, Vitomir Kovanovic, Dragan Gasevic. 605-614 [doi]
• The automated grading of student open responses in mathematicsJohn A. Erickson, Anthony F. Botelho, Steven McAteer, Ashvini Varatharaj, Neil T. Heffernan. 615-624 [doi]
• Peeking through the classroom window: a detailed data-driven analysis on the usage of a curriculum integrated math game in authentic classroomsPreya Shabrina, Ruth Okoilu Akintunde, Mehak Maniktala, Tiffany Barnes, Collin Lynch, Teomara Rutherford. 625-634 [doi]
• Data-informed curriculum sequences for a curriculum-integrated gameRuth Okoilu Akintunde, Preya Shabrina, Veronica Cateté, Tiffany Barnes, Collin Lynch, Teomara Rutherford. 635-644 [doi]
• Predicting student performance in interactive online question pools using mouse interaction featuresHuan Wei, Haotian Li, Meng Xia, Yong Wang, Huamin Qu. 645-654 [doi]
• Quantifying data sensitivity: precise demonstration of care when building student prediction modelsCharles Lang, Charlotte Woo, Jeanne Sinclair. 655-664 [doi]