A2E 2017 Abstracts


Full Papers
Paper Nr: 1
Title:

National Survey of Japanese Universities on IT Education - Overview of the Entire Project and Preliminary Analysis

Authors:

Tetsuro Kakeshita

Abstract: We are conducting a national survey of Japanese universities on IT education under the support of Japanese Mistry of Education. This paper describes the overview of the survey project and preliminary analysis of the survey result. The survey is composed of five different types: (1) survey of IT education as a major field of study, (2) survey of IT education as a part of a major field other than IT, (3) survey of general IT education for college students belonging to all faculties, (4) survey of IT education for the students willing to have a licence to be a high school teacher on IT, (5) survey of computing environment for IT education. The survey contains various questions about outline of the educational program, educational contents and achievement level for independent topic, students, teaching staff, educational environment and future plan. We collected about 3,000 answers from 650 universities using a Web-based survey system. The survey covers 85% of the Japanese universities.

Paper Nr: 3
Title:

A Characterization of Student’s Viewpoint to Learning and its Application to Learning Assistance Framework

Authors:

Toshiro Minami, Yoko Ohura and Kensuke Baba

Abstract: Due to the advancement of popularization of university education, it becomes more and more necessary for university staff to help students by enhancing their motivations to learn in addition to training study skills. We approach to this problem from lecture data analytics. We have been investigating students’ answer to a term-end retrospective questionnaire, and found students’ attitude in learning and their academic performance correlate significantly. On the basis of this finding, in this paper, we propose a framework for assisting students to improve their learning attitude. It consists of four participants; lecturer, assisting staff including librarian, data analysts, and learning assistance system built on top of learning management system. We discuss how the results of our previous studies can be utilized to assist students in this framework. Further, we introduce two indexes for measuring the weights of a student viewpoint between lecture and themselves, and between good points and bad points. These indexes show how a student’s viewpoint to the class is located in comparison with other students’ viewpoints.

Paper Nr: 4
Title:

Collecting and Analysing Learners Data to Support the Adaptive Engine of OPERA, a Learning System for Mathematics

Authors:

Marisa Oliveira, Alcinda Barreiras, Graça Marcos, Hermínia Ferreira, Ana Azevedo and Carlos Vaz de Carvalho

Abstract: Learning mathematics has always been (and still is) a major issue. Many students fail to understand the basic concepts and/or are unable to apply them. These students end up moving to other subject areas or simply dropping out. One of the major reasons for this problem is the fact that the educational system is only prepared to apply standardized teaching methods that do not respect or fit the individual characteristics of each student. This paper presents the OPERA learning adaptive system that provides the foundations for further mathematics learning while addressing the diversity of the users/learners. OPERA collects learner interaction data to monitor the learning process in an active and contextualized way and to identify the users’ difficulties and achieved knowledge in each stage. Based on the data analysis, OPERA then reorganizes the sequence of contents and provides the precise information needed to progress which makes learning much more efficient.

Short Papers
Paper Nr: 5
Title:

Learning Analytics: A Way to Monitoring and Improving Students' Learning

Authors:

Jose Manuel Azevedo, Cristina Torres, Ana Paula Lopes and Lurdes Babo

Abstract: This paper focus on the potential contributes of Learning Analytics in the improvement students learning. The analysis of student’s data collected from Virtual Learning Environments is important to ascertain student’s engagement. This paper presents the analysis of data collected in the ambit of MatActiva project. Data was analysed with Google Analytics, Course Dedication and Moodle Reports. Promising results were obtained.

Posters
Paper Nr: 6
Title:

Mapping and Identifying Features of e-Learning Technology through Indexes and Metrics

Authors:

Elias Gounopoulos, Stavros Valsamidis, Ioannis Kazanidis and Sotirios Kontogiannis

Abstract: People’ s educational needs and requirements change. At the same time, educational technologies and tools also evolve. Therefore, contemporary educational methods are obliged to adapt to both. E-learning is the mode of learning which serves the former while exploits the latter. As e-learning capabilities are moving into the third decade of their implementation (Kulik et al., 1990), the necessity of thorough assessment is imminent. Moreover, the adoption to e-learning of assessment features which were successfully used by e-commerce is also a challenging issue. In this study, a novel approach is presented and put to test. The approach tries to utilize applicable features of e-commerce technology to e-learning in an effort to measure usage, user trends and knowledge affiliations. To the extent, some already tested indexes and metrics are used for the quantification of qualitative features of e-learning. These indexes and metrics contribute to the assessment of both educational content exposed by the educators and content usage by the learners. In this paper the identified features are classified. Finally, an experimental case scenario that took place in a Greek university e-learning platform is presented. From the revealed results there is evidence that these corresponding to features variables can be used for the measurement of reach, richness and information density of an e-learning platform system.