Poster Session & Technology Showcase

Poster & Technology Showcase

The numbers / letters below indicate your order in the Firehose Session and will help you locate your poster board or demo table location in the room. The Poster Session & Technology Showcase will be held concurrently with the Welcome Reception on Wednesday evening at 4:45 in the Segal Building Founders Hall & Room 1200-1500.

Download the Posters Program with full presentation list and room map

Printed Posters

Doctoral Consortium

  1. The Design of Learning Analytics to Support a Knowledge Community and Inquiry Approach to Secondary Science
  • Alisa Acosta
  1. Digital Learning Projection: Learning state estimation from multimodal learning experiences.
  • Daniele Di Mitri
  1. Seeking Relevance: Affordances of Learning Analytics for Self-Regulated Learning
  • Tracie Farrell-Frey
  1. Learning Analytics in Noncognitive Domains
  • Danielle Hagood
  1. Designing a Learning Analytics Capabilities Model
  • Justian Knobbout
  1. The Purpose of Higher Education in the Discourse of Learning Analytics
  • Leif Nelson
  1. Unravelling the dynamics of learning design within and between disciplines in higher education using learning analytics
  • Le Quan Nguyen
  1. Design Guidelines for Blended Learning Environments to Support Self-regulation: Event Sequence Analysis for Investigating Learners’ Self-Regulatory Behavior.
  • Stijn Van Laer
  1. Students’ intentions to use technology in their learning: The effects of internal and external conditions
  • Alexander Whitelock-Wainwright
  1. Write-and-Learn: Promoting Meaningful Learning through Concept Map-Based Formative Feedback on Writing Assignments
  • Ye Xiong

Research Track Printed Posters

  1. Student Empowerment, Awareness, and Self-Regulation through a Quantified-Self Student Tool
  • Kimberly Arnold, Brandon Karcher, Casey Wright and James McKay
  1. A Framework For Hypothesis-Driven Approaches To Support Data-Driven Learning Analytics In Measuring Computational Thinking In Block-Based Programming
  • Shuchi Grover, Marie Bienkowski, Satabdi Basu, Michael Eagle, Nicholas Diana and John Stamper
  1. Learning Analytics for Sensor-Based Adaptive Learning
  • Albrecht Fortenbacher, Niels Pinkwart and Haeseon Yun
  1. Examining Motivations and Self-regulated Learning Strategies of Returning MOOCs Learners
  • Bodong Chen, Yizhou Fan, Guogang Zhang and Qiong Wang
  1. When Learning is High Stake
  • Cecilie Johanne Slokvik Hansen, Barbara Wasson, Hans Skretting, Grete Netteland and Marina Hirnstein
  1. Challenges and Opportunities Facing Educational Discourse Researchers
  • Christopher Brooks, Stephanie Teasley and George Siemens
  1. Supporting Learning Analytics in Computing Education
  • Daniel Olivares and Christopher Hundhausen
  1. Tracing physical movement during practice-based learning through Multimodal Learning Analytics
  • Donal Healion, Sam Russell, Mutlu Cukurova and Daniel Spikol
  1. Beyond Failure: The 2nd LAK Failathon Poster
  • Doug Clow, Rebecca Ferguson, Kirsty Kitto, Yong-Sang Cho, Mike Sharkey and Cecilia Aguerrebere
  1. Forecasting Student Outcomes at University-Wide Scale Using Machine Learning
  • Drew Wham
  1. Utilizing Visualization and Feature Selection Methods to Identify Important Learning Objectives in a Course
  • Farshid Marbouti, Heidi Diefes-Dux and Krishna Madhavan
  1. A Neural Network Approach for Students’ Performance Prediction
  • Fumiya Okubo, Takayoshi Yamashita, Atsushi Shimada and Hiroaki Ogata
  1. Buying Time: Enabling Learners to become Earners with a Real-World Paid Task Recommender System
  • Guanliang Chen, Daniel Davis, Markus Krause, Claudia Hauff and Geert-Jan Houben
  1. Best Intentions: Learner Feedback on Learning Analytics Visualization Design
  • Halimat Alabi and Marek Hatala
  1. What does student writing tell us about their thinking on social justice?
  • Heeryung Choi, Christopher Brooks and Kevyn Collins-Thompson
  1. The effects of a learning analytics empowered technology on the students’ arithmetic skills learning
  • Inge Molenaar, Carolien Knoop-Van Campen and Fred Hasselman
  1. Business Intelligence (BI) for Personalized Student Dashboards
  • Jody Sluijter and Marloes Otten
  1. Integrating Syllabus Data into Student Success Models
  • Josh Gardner, Ogechi Onuoha and Christopher Brooks
  1. An investigation of adaptive thresholds for speech recognition scores in English language learning
  • Josine Verhagen and Webb Phillips
  1. Topic Models to Support Instructors in MOOC Forums
  • Jovita Vytasek, Alyssa Wise and Sonya Woloshen
  1. Large Scale Predictive Process Mining and Analytics of University Degree Courses
  • Jurgen Schulte, Pedro Fernandez de Mendonca, Roberto Martinez-Maldonado and Simon Buckingham Shum
  1. Exploring the Measurement of Collaborative Problem Solving Using a Human-Agent Educational Game
  • Kristin Stoeffler, Yigal Rosen, Alina von Davier and Amit Agrawal
  1. Predicting e-Textbook Adoption Based on Event Segmentation of Teachers’ Usage
  • Longwei Zheng, Wei Gong and Xiaoqing Gu
  1. Learning from Learning Curves: Discovery of Interpretable Learning Trajectory Groups
  • Lujie Chen and Artur Dubrawski
  1. Relevance of Learning Analytics to Measure and Support Students’ Learning in Adaptive Educational Technologies
  • Maria Bannert, Inge Molenaar, Roger Azevedo, Sanna Järvelä and Dragan Gašević
  1. Using Item Response Theory to Generate an Item Pool for an E-Learning-System
  • Markus Schweighart
  1. Reproducibility of Findings from Educational Big Data: A Preliminary Study
  • Misato Oi, Masanori Yamada, Fumiya Okubo, Atsushi Shimada and Hiroaki Ogata
  1. Mining Knowledge Components From Many Untagged Questions
  • Neil Zimmerman and Ryan Baker
  1. Automated Analysis of Aspects of Written Argumentation 
  • Noureddine Elouazizi, Gülnur Birol, Eric Jandciu, Gunilla Oberg, Ashley Welsh, Andrea Han and Alice Campbell
  1. How can we accelerate dissemination of knowledge and learning?: Developing an online knowledge management platform for Networked Improvement Communities
  • Ouajdi Manai and Hiroyuki Yamada
  1. Using predictive analytics in a self-regulated learning university course to promote student success
  • Rebecca Edwards, Sarah Davis, Dr. Allyson Hadwin and Dr. Todd Milford
  1. Cooking with Learning Analytics Recipes
  • Roope Jaakonmäki, Stefan Dietze, Hendrik Drachsler, Albrecht Fortenbacher, Michael Kickmeier-Rust and Ivana Marenzi
  1. Automating Student Survey Reports in Online Education for Faculty and Instructional Designers
  • Sean Burns and Kimberley Corwin
  1. Students’ Emotional Self-Labels for Personalized Models
  • Sinem Aslan, Eda Okur, Nese Alyuz, Sinem Emine Mete, Ece Oktay, Utku Genc and Asli Arslan Esme
  1. An Automatic Approach for Discovering Skill Relationship from Learning Data
  • Tak-Lam Wong, Haoran Xie, Fu Lee Wang, Chung Keung Poon and Di Zou
  1. Discourse Analysis to Improve the Effective Engagement of MOOC Videos
  • Thushari Atapattu and Katrina Falkner
  1. Understanding the relationship between technology use and cognitive presence in MOOCs
  • Vitomir Kovanović, Srećko Joksimović, Oleksandra Poquet, Thieme Hennis, Shane Dawson, Dragan Gašević, Pieter de Vries, Marek Hatala and George Siemens
  1. Video Annotation Tool for Learning Job Interview
  • Yoshitomo Yaginuma, Masako Furukawa and Tsuneo Yamada
  1. A Systematic Review of Studies on Predicting Student Learning Outcomes Using Learning Analytics
  • Xiao Hu, Christy W.L. Cheong, Wenwen Ding and Michelle Woo
  1. Data-Assisted Instructional Video Revision via Course-Level Exploratory Video Retention Analysis
  • Chi-Un Lei, Donn Gonda, Xiangyu Hou, Elizabeth Oh, Xinyu Qi, Tyrone T.O. Kwok, Yip-Chun Au Yeung and Ray Lau

 Practitioner Track Technology Showcase

  1. Using Learning Analytics to Improve the Design of a Blended Course
  • Matt Farrell
  1. Data-Supported Learning Design: A customer care training example
  • Tanya Dorey-Elias
  1. Relationships Between Digital Measures of Student Engagement and Exam Scores: Is the LMS Enough?
  • Perry Samson, Alex Czarnik and Melissa Gross

 

Powered Posters / Demos

 Practitioner Track Technology Showcase

A. Piloting Learning Analytics to Support Differentiated Learning through LearningANTS

  • Edna Chan, Say-Beng Lai, May Lim, Ying-Ying Soh and Ah-Choo Tan-Yeoh

B. Competency Map

  • Jeff Grann

C. Jupyter Notebooks at Scale

  • Amory Schlender and Kara Behnke

D. Measuring Learner Engagement

  • Sean Yo, Amrita Thakur and Mitchell Deleplanque

E. M2B System: A Digital Learning Platform for Traditional Classrooms in University

  • Hiroaki Ogata, Yuta Taniguchi, Daiki Suehiro, Atsushi Shimada, Misato Oi, Fumiya Okubo, Masanori Yamada and Kentaro Kojima

F. OUAnalyse: Scalable Learning Analytics at The Open University

  • Martin Hlosta, Zdenek Zdrahal, Jakub Kužílek and Michal Huptych

G. Identifying Non-Regulators: Designing and Deploying Tools that Detect Self-Regulation Behaviors

  • Mary Pilgrim, James Folkestad and Ben Sencindiver

  Research Track Powered Posters

H. New Features in Wikiglass, A Learning Analytic Tool for Visualizing Collaborative Work on Wikis

  • Xiao Hu, Chengrui Yang, Chen Qiao, Xiaoyu Lu and Samuel Chu

I. An Outcome-based Dashboard for Moodle and Open EdX

  • Xiao Hu, Xiangyu Hou, Chi-Un Lei, Chengrui Yang and Tzi Dong Jeremy Ng

J. Using Learning Analytics in Iterative Design of a Digital Modeling Tool

  • David Quigley, Conor McNamara and Tamara Sumner

K. Ambient Analytics: Reflecting Data in Educational Spaces

  • Tushar Kochgavay, Christopher Brooks, Elijah Sattler and Evan Brisita

L. What Are Visitors Up To? Helping Museum Facilitators Know What Visitors are Doing

  • Vishesh Kumar, Mike Tissenbaum and Matthew Berland

M. MORPH: Supporting the Integration of Learning Analytics at Institutional Level

  • Zoran Jeremic, Vive Kumar and Sabine Graf

 

 

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