| 13:30 – 15:00 |
“Learning analytics, technologies and tools to support smart learning environments” Session
Session Chair: Nian-Shing Chen
Paper-12F
The effects of student interaction with blog-based course content on learning performance
Benazir Quadir, Jie Chi Yang, Jun Zhang, and Houli Gao
Paper-14S
Innovative Maker Movement Platform for K-12 Education as a Smart Learning Environment
Tapani Toivonen, Ilkka Jormanainen, Calkin Suero Montero, and Andrea Alessandrini
Paper-21F
StudentViz: A Tool for Visualizing Students’ Collaborations in a Social Learning Environment
Alex Becheru, Andreea Calota, and Elvira Popescu
Paper-23S
Constructing a Smart Chinese International Learning Environment Based on Learning Analytics Technology
Juan Xu, Yanlan Shi, and Yongbin Zhou |
| 15:20 – 16:50 |
“Assessment and gamification in smart learning environments” Session
Session Chair: Erik Isaksson
Paper-05S
The Objective Ear: Assessing the Progress of a Music Task
Joel Burrows, and Vivekanandan Kumar
Paper-19F
The Edutainment Platform: Interactive Storytelling Relying on Semantic Similarity
Irina Toma, Florentina Bacioiu, Mihai Dascalu, and Stefan Trausan-Matu
Paper-22F
A Gamified Approach to Automated Assessment of Programming Assignments
Giuseppina Polito, and Marco Temperini
Paper-26F
Higher Cognitive Items Generation Algorithms
Ebenezer Aggrey, Maiga Chang, Rita Kuo, and Xiaokun Zhang |
| 16:50 – 17:50 |
Poster Session
Session Chair: Maiga Chang and Elvira Popescu
Paper-04P
An interdisciplinary Framework for Designing Smart Learning Environments
Sirkka Freigang, Lars Schlenker, and Thomas Köhler
Paper-06P
Smart watches for making EFL learning effective, healthy, and happy
Rustam Shadiev, Wu-Yuin Hwang, Narzikul Shadiev, Mirzaali Fayziev, Tzu-Yu Liu, and Lingjie Shen
Paper-08P
Application Development on Tablet to Promote a Classroom Research Skills for SSRU’ Students
Chaiwat Waree
Paper-13P
A Smart Learning Environment for Environmental Education
Ilkka Jormanainen, Tapani Toivonen, and Ville Nivalainen |
| 10:30 – 12:00 |
“Innovative uses of emerging and existing technologies” Session
Session Chair: Rustam Shadiev
Paper-16F
Effects of Reciprocal Feedback on EFL Learners’ Communication Strategy Use and Oral Communicative Performance
Sie Wai Chew, Wei-Chieh Fang, Chia-Ning Hsu, and Nian-Shing Chen
Paper-17S
Visualizing and Understanding Information literacy Research Based on the CiteSpaceV
Liqin Yu, Di Wu, Sha Zhu, and Huan Li
Paper-18S
Smart Interactions for the Quantified Self
Erik Isaksson, and Björn Hedin
Paper-20F
Exploring General Morphological Analysis and Providing Personalized Recommendations to Stimulate Creativity with ReaderBench
Daniela Stamati, Maria-Dorinela Sirbu, Mihai Dascalu, and Stefan Trausan-Matu |
| 13:30 – 15:50 |
2nd International Workshop on Technology Assist Teaching and Administration
Workshop Chair: Maiga Chang, Athabasca University, Canada
13:30-13:35
Introduction
TATA is an interactive/tutorial like workshop. In the first session, researchers of each accepted workshop paper will introduce the technologies from practical point of views (instead of talking theories, maths, and detailed methods) for 10 to 15 minutes. Then, the workshop gives participants 20 to 25 minutes to really try on the proposed systems and tools. At the end, researchers can further interact with participants in the 10 to 15 minutes discussion section so the participants can share their perceptions, comments, suggestions, and even intention of using the proposed systems and tools with researchers.
13:35-14:20
An educational role-playing game for modeling the learner’s personality
Mouna Denden, Ahmed Tlili, Fathi Essalmi, and Mohamed Jemni
Recently, there has been an increasing interest in learner modeling in order to provide personalized computer based learning experiences. Generally, researchers and practitioners use questionnaires as a method to model learners, including their personalities, which can be time consuming and not motivating. Therefore, the research team presents a new approach for modeling the learner’s personality, specifically introvert/extrovert, using an online educational game and Learning Analytics (LA) system.
14:20-15:05
Annotation Recommendation for Online Reading Activities
Miao-Han Chang, Maiga Chang, Rita Kuo, Fathi Essalmi, Vivekanandan S. Kumar, and Hsu-Yang Kung
Both classroom and online learning ask students doing reading activities. The mature and widely used e-readers allow students reading and making annotation on the screen with their computer, tablet, or even smartphone. Annotations will be a very important resource aside from the notes for students while preparing for exams. However, sometimes students might think something is not important or relevant or just simply overlook while making annotations on the materials. Such annotations might lead to lose marks later when they are writing exams. The research team has developed an online annotation system that allows teachers to create online reading activities for their students and review students’ annotations on the e-text. Moreover, with the help of a bio-inspired innovative clustering method GRACE (General Rapid Annotation Clustering Enhancement), students will be offered annotation recommendations based on the similarity their annotations have from other students on the same text. In such case, students may reconsider the content they chose to ignore or overlooked earlier and make their annotations more complete and better for exam preparation later.
15:05-15:50
Big Data Analytics and Smart Service Tool: “Smart Learning Partner” Platform
Xiaoqing Li, Linghong Du, and Xuanwei Ma
In order to collect students’ big data during learning process, model their knowledge and capability structures, and provide the individualized service based on the data, Advanced Innovation Center for Future Education of Beijing Normal University has researched and developed a big data analytics and smart service platform, Smart Learning Partner (SLP). The research team introduces and analyzes the SLP platform and its representative characteristics as well as explains the hidden logic of its smart service, thereby providing a reference for educators to draw upon when carrying out personalized research. |
| 16:10 – 16:50 |
Tutorial: Open Research and Observational Study for 21st Century Learning
Tutorial Chair: Vive Kumar, Athabasca University, Canada
This presentation introduces Open Research in the context of Smart Learning. First, it discusses the advantages of opening the research process to an authorized public, fellow students, educators and policymakers. For example, it argues that greater accessibility can promote research growth and integrity. Second, it uses observational study methods to illustrate the ways students and educators can conduct their own experiments using continuously arriving data. This second section introduces three matching techniques (i.e. Coarsened Exact Matching, Mahalanobis Distance Matching, and Propensity Score Matching) and three data imbalance metrics (i.e. L1 vector norm, Average Mahalanobis Imbalance, and Difference in Means) to assess the level of data imbalance within matched sample datasets. Ultimately, the presentation promotes Smart Learning Environments that incorporate automated tools for opportunistic capture, analysis and remediation of various formative study processes. Such environments can enable students to ethically share and receive study data that help them conduct personal observational studies on individual study related questions. Moreover, it explains key traits of observational studies that are relevant for smart learning environments, considering the comparable traits of blocked randomized experiments. Remarkably, this presentation proposes a novel idea to connect Open Research with Persistent Observational Study methods. It explores how open research can support adaptive and self-regulated learning. It advocates for innovative research practices that can produce better and smarter learning. |