Abstract is missing.
- Developing a MOOC experimentation platform: insights from a user studyVitomir Kovanovic, Srecko Joksimovic, Philip Katerinopoulos, Charalampos Michail, George Siemens, Dragan Gasevic. 1-5 [doi]
- Ouroboros: early identification of at-risk students without models based on legacy dataMartin Hlosta, Zdenek Zdráhal, Jaroslav Zendulka. 6-15 [doi]
- Impact of student choice of content adoption delay on course outcomesLalitha Agnihotri, Alfred Essa, Ryan S. Baker. 16-20 [doi]
- Detecting changes in student behavior from clickstream dataJihyun Park, Kameryn Denaro, Fernando Rodriguez, Padhraic Smyth, Mark Warschauer. 21-30 [doi]
- Modeling exploration strategies to predict student performance within a learning environment and beyondTanja Käser, Nicole R. Hallinen, Daniel L. Schwartz. 31-40 [doi]
- Opportunities for personalization in modeling students as Bayesian learnersCharles Lang. 41-45 [doi]
- An elephant in the learning analytics room: the obligation to actPaul Prinsloo, Sharon Slade. 46-55 [doi]
- Where is the evidence?: a call to action for learning analyticsRebecca Ferguson, Doug Clow. 56-65 [doi]
- Student perceptions of their privacy in leaning analytics applicationsKimberly E. Arnold, Niall Sclater. 66-69 [doi]
- Understanding student learning trajectories using multimodal learning analytics within an embodied-interaction learning environmentAlejandro Andrade. 70-79 [doi]
- Put your thinking cap on: detecting cognitive load using EEG during learningCaitlin Mills, Igor Fridman, Walid Soussou, Disha Waghray, Andrew McGregor Olney, Sidney K. D'Mello. 80-89 [doi]
- Analytics meet patient manikins: challenges in an authentic small-group healthcare simulation classroomRoberto Martínez Maldonado, Tamara Power, Carolyn Hayes, Adrian Abdiprano, Tony Vo, Simon Buckingham Shum. 90-94 [doi]
- How to assign students into sections to raise learningMing Ming Chiu, Bonnie Wing-Yin Chow, Sung Wook Joh. 95-104 [doi]
- Improving learning through achievement priming in crowdsourced information finding microtasksUjwal Gadiraju, Stefan Dietze. 105-114 [doi]
- Exploring the asymmetry of metacognitionAni Aghababyan, Nicholas Lewkow, Ryan S. Baker. 115-119 [doi]
- Temporal analytics with discourse analysis: tracing ideas and impact on communal discourseAlwyn Vwen Yen Lee, Seng Chee Tan. 120-127 [doi]
- Dynamics of MOOC discussion forumsMina Shirvani Boroujeni, Tobias Hecking, Heinz Ulrich Hoppe, Pierre Dillenbourg. 128-137 [doi]
- Assessment of language in authentic science inquiry reveals putative differences in epistemologyMelanie E. Peffer, Kristopher Kyle. 138-142 [doi]
- Predicting the decrease of engagement indicators in a MOOCMiguel L. Bote-Lorenzo, Eduardo Gómez-Sánchez. 143-147 [doi]
- Studying engagement and performance with learning technology in an African classroomJuliet Mutahi, Andrew Kinai, Nelson Bore, Abdigani Diriye, Komminist Weldemariam. 148-152 [doi]
- Reflective writing analytics for actionable feedbackAndrew Gibson, Adam Aitken, Ágnes Sándor, Simon Buckingham Shum, Cherie Tsingos-Lucas, Simon Knight. 153-162 [doi]
- Reflective writing analytics: empirically determined keywords of written reflectionThomas Daniel Ullmann. 163-167 [doi]
- Unravelling the dynamics of instructional practice: a longitudinal study on learning design and VLE activitiesQuan Nguyen, Bart Rienties, Lisette Toetenel. 168-177 [doi]
- Sequencing content in an adaptive testing system: the role of choiceSeth Akonor Adjei, Anthony F. Botelho, Neil T. Heffernan. 178-182 [doi]
- ATCE: an analytics tool to trace the creation and evaluation of inclusive and accessible open educational resourcesCecilia Ávila, Silvia Baldiris, Ramón Fabregat, Sabine Graf. 183-187 [doi]
- Learning pulse: a machine learning approach for predicting performance in self-regulated learning using multimodal dataDaniele Di Mitri, Maren Scheffel, Hendrik Drachsler, Dirk Börner, Stefaan Ternier, Marcus Specht. 188-197 [doi]
- Transitioning self-regulated learning profiles in hypermedia-learning environmentsClarissa Lau, Jeanne Sinclair, Michelle Taub, Roger Azevedo, Eunice Eunhee Jang. 198-202 [doi]
- Expanding the scope of learning analytics data: preliminary findings on attention and self-regulation using wearable technologyCatherine A. Spann, James Schaeffer, George Siemens. 203-207 [doi]
- How effective is your facilitation?: group-level analytics of MOOC forumsOleksandra Poquet, Shane Dawson, Nia Dowell. 208-217 [doi]
- Words matter: automatic detection of teacher questions in live classroom discourse using linguistics, acoustics, and contextPatrick J. Donnelly, Nathaniel Blanchard, Andrew McGregor Olney, Sean Kelly, Martin Nystrand, Sidney K. D'Mello. 218-227 [doi]
- Towards mining sequences and dispersion of rhetorical moves in student written textsSimon Knight, Roberto Martínez Maldonado, Andrew Gibson, Simon Buckingham Shum. 228-232 [doi]
- Learning analytics in higher education - challenges and policies: a review of eight learning analytics policiesYi-Shan Tsai, Dragan Gasevic. 233-242 [doi]
- The influence of data protection and privacy frameworks on the design of learning analytics systemsTore Hoel, Dai Griffiths, Weiqin Chen. 243-252 [doi]
- An information policy perspective on learning analyticsCaroline Haythornthwaite. 253-256 [doi]
- Intelligent tutors as teachers' aides: exploring teacher needs for real-time analytics in blended classroomsKenneth Holstein, Bruce M. McLaren, Vincent Aleven. 257-266 [doi]
- Implementing predictive learning analytics on a large scale: the teacher's perspectiveChristothea Herodotou, Bart Rienties, Avinash Boroowa, Zdenek Zdráhal, Martin Hlosta, Galina Naydenova. 267-271 [doi]
- An instructor dashboard for real-time analytics in interactive programming assignmentsNicholas Diana, Michael Eagle, John C. Stamper, Shuchi Grover, Marie A. Bienkowski, Satabdi Basu. 272-279 [doi]
- Real-time learning analytics for C programming language coursesXinyu Fu, Atsushi Shimada, Hiroaki Ogata, Yuta Taniguchi, Daiki Suehiro. 280-288 [doi]
- Widget, widget as you lead, I am performing well indeed!: using results from an exploratory offline study to inform an empirical online study about a learning analytics widget in a collaborative learning environmentMaren Scheffel, Hendrik Drachsler, Karel Kreijns, Joop De Kraker, Marcus Specht. 289-298 [doi]
- Building a transcript of the futureBenjamin P. Koester, James Fogel, William Murdock III, Galina Grom, Timothy A. McKay. 299-308 [doi]
- Trends and issues in student-facing learning analytics reporting systems researchRobert Bodily, Katrien Verbert. 309-318 [doi]
- Uncovering reviewing and reflecting behaviors from paper-based formal assessmentI-Han Hsiao, Po-Kai Huang, Hannah Murphy. 319-328 [doi]
- Scientific modeling: using learning analytics to examine student practices and classroom variationDavid Quigley, Jonathan L. Ostwald, Tamara Sumner. 329-338 [doi]
- Predicting math performance using natural language processing toolsScott A. Crossley, Ran Liu, Danielle S. McNamara. 339-347 [doi]
- Learning analytics in a seamless learning environmentKousuke Mouri, Hiroaki Ogata, Noriko Uosaki. 348-357 [doi]
- SPACLE: investigating learning across virtual and physical spaces using spatial replaysKenneth Holstein, Bruce M. McLaren, Vincent Aleven. 358-367 [doi]
- What do students want?: towards an instrument for students' evaluation of quality of learning analytics servicesAlexander Whitelock-Wainwright, Dragan Gasevic, Ricardo Tejeiro. 368-372 [doi]
- What'd you say again?: recurrence quantification analysis as a method for analyzing the dynamics of discourse in a reading strategy tutorLaura K. Allen, Cecile A. Perret, Aaron D. Likens, Danielle S. McNamara. 373-382 [doi]
- Honing in on social learning networks in MOOC forums: examining critical network definition decisionsAlyssa Friend Wise, Yi Cui, Wan Qi Jin. 383-392 [doi]
- Using correlational topic modeling for automated topic identification in intelligent tutoring systemsStefan Slater, Ryan S. Baker, Ma. Victoria Almeda, Alex J. Bowers, Neil T. Heffernan. 393-397 [doi]
- Enhancing learning through virtual reality and neurofeedback: a first stepRyan Hubbard, Aldis Sipolins, Lin Zhou. 398-403 [doi]
- Measures for recommendations based on past students' activityMichal Huptych, Michal Bohuslavek, Martin Hlosta, Zdenek Zdráhal. 404-408 [doi]
- Supporting collaborative learning with tag recommendations: a real-world study in an inquiry-based classroom projectSimone Kopeinik, Elisabeth Lex, Paul Seitlinger, Dietrich Albert, Tobias Ley. 409-418 [doi]
- Classifying help seeking behaviour in online communitiesSebastian Cross, Zak Waters, Kirsty Kitto, Guido Zuccon. 419-423 [doi]
- Using learning analytics to explore help-seeking learner profiles in MOOCsLinda Corrin, Paula de Barba, Aneesha Bakharia. 424-428 [doi]
- EMODA: a tutor oriented multimodal and contextual emotional dashboardMohamed Ez-zaouia, Élise Lavoué. 429-438 [doi]
- Person-centered approach to explore learner's emotionality in learning within a 3D narrative gameZhenhua Xu, Earl Woodruff. 439-443 [doi]
- Using data visualizations to foster emotion regulation during self-regulated learning with advanced learning technologies: a conceptual frameworkRoger Azevedo, Garrett C. Millar, Michelle Taub, Nicholas V. Mudrick, Amanda E. Bradbury, Megan J. Price. 444-448 [doi]
- Strategies for data and learning analytics informed national education policies: the case of UruguayCecilia Aguerrebere, Cristóbal Cobo, Marcela Gomez, Matías Mateu. 449-453 [doi]
- Follow the successful crowd: raising MOOC completion rates through social comparison at scaleDan Davis, Ioana Jivet, René F. Kizilcec, Guanliang Chen, Claudia Hauff, Geert-Jan Houben. 454-463 [doi]
- Planning prompts increase and forecast course completion in massive open online coursesMichael Yeomans, Justin Reich. 464-473 [doi]
- From prediction to impact: evaluation of a learning analytics retention programShane Dawson, Jelena Jovanovic, Dragan Gasevic, Abelardo Pardo. 474-478 [doi]
- Guidance counselor reports of the ASSISTments college prediction model (ACPM)Jaclyn Ocumpaugh, Ryan S. Baker, Maria Ofelia Clarissa Z. San Pedro, M. Aaron Hawn, Cristina Heffernan, Neil T. Heffernan, Stefan A. Slater. 479-488 [doi]
- Don't call it a comeback: academic recovery and the timing of educational technology adoptionMichael Geoffrey Brown, R. Matthew DeMonbrun, Stephanie D. Teasley. 489-493 [doi]
- LA policy: developing an institutional policy for learning analytics using the RAPID outcome mapping approachYi-Shan Tsai, Dragan Gasevic, Pedro J. Muñoz Merino, Shane Dawson. 494-495 [doi]
- Writing analytics literacy: bridging from research to practiceSimon Knight, Laura K. Allen, Andrew Gibson, Danielle S. McNamara, Simon Buckingham Shum. 496-497 [doi]
- Developing institutional learning analytics 'communities of transformation' to support student successLeah Macfadyen, Dennis Groth, George Rehrey, Linda Shepard, Jim E. Greer, Douglas Ward, Caroline Bennett, Jake Kaupp, Marco Molinaro, Matthew Steinwachs. 498-499 [doi]
- Workshop on methodology in learning analytics (MLA)Yoav Bergner, Charles Lang, Geraldine Gray. 500-501 [doi]
- Quasi-experimental design for causal inference using Python and Apache Spark: a hands-on tutorialShirin Mojarad, Nicholas Lewkow, Alfred Essa, Jie Zhang, Jacqueline L. Feild. 502-503 [doi]
- nd LAK FailathonDoug Clow, Rebecca Ferguson, Kirsty Kitto, Yong-Sang Cho, Mike Sharkey, Cecilia Aguerrebere. 504-505 [doi]
- Workshop on integrated learning analytics of MOOC post-course developmentYuan Wang, Dan Davis, Guanliang Chen, Luc Paquette. 506-507 [doi]
- DesignLAK17: quality metrics and indicators for analytics of assessment design at scaleUlla Ringtved, Sandra Milligan, Linda Corrin, Allison Littlejohn, Nancy Law. 508-509 [doi]
- nd cross-LAK: learning analytics across physical and digital spacesRoberto Martínez Maldonado, Davinia Hernández Leo, Abelardo Pardo, Hiroaki Ogata. 510-511 [doi]
- FutureLearn data: what we currently have, what we are learning and how it is demonstrating learning in MOOCsLorenzo Vigentini, Manuel Leon Urrutia, Ben Fields. 512-513 [doi]
- LAK17 hackathon: getting the right information to the right people so they can take the right actionAdam Cooper, Alan Berg, Niall Sclater, Tanya Dorey-Elias, Kirsty Kitto. 514-515 [doi]
- Learning analytics and policy (LAP): international aspirations, achievements and constraintsMegan Bowe, Weiqin Chen, Dai Griffiths, Tore Hoel, Jaeho Lee, Hiroaki Ogata, Griff Richards, Li Yuan, Jingjing Zhang. 516-517 [doi]
- Current and future multimodal learning analytics data challengesDaniel Spikol, Luis Pablo Prieto, María Jesús Rodríguez-Triana, Marcelo Worsley, Xavier Ochoa, Mutlu Cukurova. 518-519 [doi]
- Building the learning analytics curriculum: workshopCharles Lang, Stephanie D. Teasley, John C. Stamper. 520-521 [doi]
- Connecting data with student support actions in a course: a hands-on tutorialAbelardo Pardo, Roberto Martínez Maldonado, Simon Buckingham Shum, Jurgen Schulte, Simon McIntyre, Dragan Gasevic, Jing Gao, George Siemens. 522-523 [doi]
- Community based educational data repositories and analysis toolsKen Koedinger, Ran Liu, John C. Stamper, Candace Thille, Phil Pavlik. 524-525 [doi]
- Student empowerment, awareness, and self-regulation through a quantified-self student toolKimberly E. Arnold, Brandon Karcher, Casey V. Wright, James McKay. 526-527 [doi]
- A systematic review of studies on predicting student learning outcomes using learning analyticsXiao Hu, Christy W. L. Cheong, Wenwen Ding, Michelle Woo. 528-529 [doi]
- A framework for hypothesis-driven approaches to support data-driven learning analytics in measuring computational thinking in block-based programmingShuchi Grover, Marie A. Bienkowski, Satabdi Basu, Michael Eagle, Nicholas Diana, John C. Stamper. 530-531 [doi]
- Dear learner: participatory visualisation of learning data for sensemakingSimon Knight, Theresa D. Anderson, Kelly Tall. 532-533 [doi]
- Video annotation tool for learning job interviewYoshitomo Yaginuma, Masako Furukawa, Tsuneo Yamada. 534-535 [doi]
- Reproducibility of findings from educational big data: a preliminary studyMisato Oi, Masanori Yamada, Fumiya Okubo, Atsushi Shimada, Hiroaki Ogata. 536-537 [doi]
- Large scale predictive process mining and analytics of university degree course dataJurgen Schulte, Pedro Fernandez de Mendonca, Roberto Martínez Maldonado, Simon Buckingham Shum. 538-539 [doi]
- nd LAK Failathon posterDoug Clow, Rebecca Ferguson, Kirsty Kitto, Yong-Sang Cho, Mike Sharkey, Cecilia Aguerrebere. 540-541 [doi]
- Examining motivations and self-regulated learning strategies of returning MOOCs learnersBodong Chen, Yizhou Fan, Guogang Zhang, Qiong Wang. 542-543 [doi]
- Learning from learning curves: discovering interpretable learning trajectoriesLujie Chen, Artur Dubrawski. 544-545 [doi]
- Utilizing visualization and feature selection methods to identify important learning objectives in a courseFarshid Marbouti, Heidi A. Diefes-Dux, Krishna Madhavan. 546-547 [doi]
- How can we accelerate dissemination of knowledge and learning?: developing an online knowledge management platform for networked improvement communitiesOuajdi Manai, Hiroyuki Yamada. 548-549 [doi]
- Students' emotional self-labels for personalized modelsSinem Aslan, Eda Okur, Nese Alyüz, Sinem Emine Mete, Ece Oktay, Utku Genc, Asli Arslan Esme. 550-551 [doi]
- Write-and-learn: promoting meaningful learning through concept map-based formative feedback on writing assignmentsYe Xiong, Yi-fang Brook Wu. 552-553 [doi]
- Data-assisted instructional video revision via course-level exploratory video retention analysisChi-Un Lei, Donn Gonda, Xiangyu Hou, Elizabeth Oh, Xinyu Qi, Tyrone T. O. Kwok, Yip-Chun Au Yeung, Ray Lau. 554-555 [doi]
- Using predictive analytics in a self-regulated learning university course to promote student successRebecca L. Edwards, Sarah K. Davis, Allyson F. Hadwin, Todd M. Milford. 556-557 [doi]
- What are visitors up to?: helping museum facilitators know what visitors are doingVishesh Kumar, Mike Tissenbaum, Matthew Berland. 558-559 [doi]
- Predicting e-textbook adoption based on event segmentation of teachers' usageLongwei Zheng, Wei Gong, Xiaoqing Gu. 560-561 [doi]
- Business intelligence (BI) for personalized student dashboardsJ. Sluijter, M. Otten. 562-563 [doi]
- When learning is high stakeCecilie Johanne Slokvik Hansen, Barbara Wasson, Hans Skretting, Grete Netteland, Marina Hirnstein. 564-565 [doi]
- Mining knowledge components from many untagged questionsNeil L. Zimmerman, Ryan S. Baker. 566-567 [doi]
- Relevance of learning analytics to measure and support students' learning in adaptive educational technologiesMaria Bannert, Inge Molenar, Roger Azevedo, Sanna Järvelä, Dragan Gasevic. 568-569 [doi]
- Exploring the measurement of collaborative problem solving using a human-agent educational gameKristin Stoeffler, Yigal Rosen, Alina Von Davier. 570-571 [doi]
- Cooking with learning analytics recipesRoope Jaakonmäki, Hendrik Drachsler, Michael D. Kickmeier-Rust, Stefan Dietze, Albrecht Fortenbacher, Ivana Marenzi. 572-573 [doi]
- Using item response theory to generate an item pool for an e-learning-systemM. Schweighart. 574-575 [doi]
- Forecasting student outcomes at university-wide scale using machine learningDrew Wham. 576-577 [doi]
- Buying time: enabling learners to become earners with a real-world paid task recommender systemGuanliang Chen, Dan Davis, Markus Krause, Claudia Hauff, Geert-Jan Houben. 578-579 [doi]
- Discourse analysis to improve the effective engagement of MOOC videosThushari Atapattu, Katrina E. Falkner. 580-581 [doi]
- Understanding the relationship between technology use and cognitive presence in MOOCsVitomir Kovanovic, Srecko Joksimovic, Oleksandra Poquet, Thieme Hennis, Shane Dawson, Dragan Gasevic. 582-583 [doi]
- Supporting learning analytics in computing educationDaniel M. Olivares, Christopher D. Hundhausen. 584-585 [doi]
- Integrating syllabus data into student success modelsJosh Gardner, Ogechi Onuoha, Christopher Brooks. 586-587 [doi]
- Tracing physical movement during practice-based learning through multimodal learning analyticsDonal Healion, Sam Russell, Mutlu Cukurova, Daniel Spikol. 588-589 [doi]
- Automating student survey reports in online education for faculty and instructional designersSean Burns, Kimberley Corwin. 590-591 [doi]
- [LISA] learning analytics for sensor-based adaptive learningAlbrecht Fortenbacher, Niels Pinkwart, Haeseon Yun. 592-593 [doi]
- What does student writing tell us about their thinking on social justice?Heeryung Choi, Christopher Brooks, Kevyn Collins-Thompson. 594-595 [doi]
- MORPH: supporting the integration of learning analytics at institutional levelZoran Jeremic, Vive Kumar, Sabine Graf. 596-597 [doi]
- A neural network approach for students' performance predictionFumiya Okubo, T. Yamashita, Atsushi Shimada, Hiroaki Ogata. 598-599 [doi]
- Challenges and opportunities facing educational discourse researchersChristopher A. Brooks, Stephanie D. Teasley, George Siemens. 600-601 [doi]
- Using learning analytics in iterative design of a digital modeling toolDavid Quigley, Conor McNamara, Tamara Sumner. 602-603 [doi]
- An outcome-based dashboard for moodle and Open edXXiao Hu, Xiangyu Hou, Chi-Un Lei, Chengrui Yang, Tzi-Dong Jeremy Ng. 604-605 [doi]
- Automated analysis of aspects of written argumentationNoureddine Elouazizi, Gülnur Birol, Eric Jandciu, Gunilla Öberg, Ashley Welsh, Andrea Han, Alice Campbell. 606-607 [doi]
- An automatic approach for discovering skill relationship from learning dataTak-Lam Wong, Haoran Xie, Fu Lee Wang, Chung Keung Poon, Di Zou. 608-609 [doi]
- Topic models to support instructors in MOOC forumsJovita M. Vytasek, Alyssa Friend Wise, Sonya Woloshen. 610-611 [doi]
- Best intentions: learner feedback on learning analytics visualization designHalimat Alabi, Marek Hatala. 612-613 [doi]
- The effects of a learning analytics empowered technology on students' arithmetic skill developmentInge Molenaar, Carolien Knoop van Campen, Fred Hasselman. 614-615 [doi]
- New features in Wikiglass, a learning analytic tool for visualizing collaborative work on wikisXiao Hu, Chengrui Yang, Chen Qiao, Xiaoyu Lu, Sam K. W. Chu. 616-617 [doi]