Special Issue "Adaptive Educational Technology Systems"

A special issue of Systems (ISSN 2079-8954).

Deadline for manuscript submissions: closed (31 January 2016)

Special Issue Editors

Guest Editor
Dr. Nguyen-Thinh Le

Department of Informatics, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany
Website | E-Mail
Guest Editor
Dr. Jon Mason

School of Education, Charles Darwin University Ellengowan Drive, Brinkin, Australia; Department of e-Learning, Graduate School, Korea National Open University, Seoul, South Korea
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Guest Editor
Dr. Christian Gütl

Institute of Information Systems and Computer Media, Graz University of Technology, Austria School of Information Systems, Curtin University. Perth, WA, Australia
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Guest Editor
Prof. Dr. Kiyoshi Nakabayashi

Department of Information and Network Science, Faculty of Information and Computer Science, Chiba Institute of Technology, Japan
E-Mail

Special Issue Information

Dear Colleagues,

Adaptivity is a key capability of effective instructors. The goal of many human instructors is to adapt their instruction to the needs of individual students. For example, adaptive instructors might typically collect and process information about their students’ knowledge, abilities, aspirations, and social background. In reality, however, human instructors may not be able to gather sufficient information relating to all their students at the same time, regardless of class size. With the uptake of mass education, for instance, through Massive Online Open Courses (MOOC), the need for adaptive instruction becomes more important.

As a solution, adaptive educational systems can assist human instructors in collecting and analyzing data related to student learning, so as to respond with appropriate instructional approaches. In some cases, adaptive educational systems may be superior to human instructors, due to their fast computational ability. As a result, many types of adaptive educational systems have been developed and numerous new types of applications have been proposed in the state of the art.

The challenge of developing adaptive educational systems has two complementary foci. First, the field needs to see innovative and highly effective tools that collect student data through as many human sensory input channels as possible and to analyze these data accurately. Second, human instructors working with existing and emerging tools need support on several fronts: integrating these tools into their educational practices, customizing and restructuring learning activities, and creating novel pathways to learning.

This Special Issue seeks innovative contributions on both technical and pedagogical aspects of the design, development, and evaluation of adaptive educational systems. In addition, literature review papers that provide a thorough overview of the state of the art concerning some aspects of the above-mentioned problems are also welcome.

Dr. Nguyen-Thinh Le
Dr. Jon Mason
Dr. Christian Gütl
Prof. Dr. Kiyoshi Nakabayashi
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Systems is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 350 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.


Keywords

  • inquiry-based systems
  • learning analytics
  • automated question generation
  • sense-making & the human computer interface
  • adaptive dialogue systems
  • adaptive assessment systems
  • adaptive feedback generation systems
  • adaptive modelling techniques
  • adaptive MOOC

Published Papers (6 papers)

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Research

Open AccessArticle Adaptation in E-Learning Content Specifications with Dynamic Sharable Objects
Systems 2016, 4(2), 24; doi:10.3390/systems4020024
Received: 24 February 2016 / Revised: 20 May 2016 / Accepted: 2 June 2016 / Published: 8 June 2016
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Abstract
Dynamic sophisticated real-time adaptation is not possible with current e-learning technologies. Our proposal is based on changing the approach for the development of e-learning systems using dynamic languages and including them in both platforms and learning content specifications thereby making them adaptive. We
[...] Read more.
Dynamic sophisticated real-time adaptation is not possible with current e-learning technologies. Our proposal is based on changing the approach for the development of e-learning systems using dynamic languages and including them in both platforms and learning content specifications thereby making them adaptive. We propose a Sharable Auto-Adaptive Learning Object (SALO), defined as an object that includes learning content and describes its own behaviour supported by dynamic languages. We describe an example implementation of SALO for the delivery and assessment of a web development course using Moodle rubrics. As a result, the learning objects can dynamically adapt their characteristics and behaviour in e-learning platforms. Full article
(This article belongs to the Special Issue Adaptive Educational Technology Systems)
Open AccessArticle A Classification of Adaptive Feedback in Educational Systems for Programming
Systems 2016, 4(2), 22; doi:10.3390/systems4020022
Received: 23 December 2015 / Revised: 28 April 2016 / Accepted: 5 May 2016 / Published: 23 May 2016
Cited by 1 | PDF Full-text (306 KB) | HTML Full-text | XML Full-text
Abstract
Over the last three decades, many educational systems for programming have been developed to support learning/teaching programming. In this paper, feedback types that are supported by existing educational systems for programming are classified. In order to be able to provide feedback, educational systems
[...] Read more.
Over the last three decades, many educational systems for programming have been developed to support learning/teaching programming. In this paper, feedback types that are supported by existing educational systems for programming are classified. In order to be able to provide feedback, educational systems for programming deployed various approaches to analyzing students’ programs. This paper identifies analysis approaches for programs and introduces a classification for adaptive feedback supported by educational systems for programming. The classification of feedback is the contribution of this paper. Full article
(This article belongs to the Special Issue Adaptive Educational Technology Systems)
Open AccessArticle A Knowledge Comparison Environment for Supporting Meaningful Learning of E-Book Users
Systems 2016, 4(2), 21; doi:10.3390/systems4020021
Received: 31 January 2016 / Revised: 27 April 2016 / Accepted: 28 April 2016 / Published: 16 May 2016
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Abstract
In this paper, we present an ontology-based visualization support system which can provide a meaningful learning environment to help e-book learners to effectively construct their knowledge frameworks. In this personalized visualization support system, learners are encouraged to actively locate new knowledge in their
[...] Read more.
In this paper, we present an ontology-based visualization support system which can provide a meaningful learning environment to help e-book learners to effectively construct their knowledge frameworks. In this personalized visualization support system, learners are encouraged to actively locate new knowledge in their own knowledge framework and check the logical consistency of their ideas for clearing up misunderstandings; on the other hand, instructors will be able to decide the group distribution for collaborative learning activities based on the knowledge structure of learners. For facilitating those visualization supports, a method to semi-automatically construct a course-centered ontology to describe the required information in a map structure is presented. To automatically manipulate this course-centered ontology to provide visualization learning supports, a prototype system is designed and developed. Full article
(This article belongs to the Special Issue Adaptive Educational Technology Systems)
Open AccessArticle When Easy Becomes Boring and Difficult Becomes Frustrating: Disentangling the Effects of Item Difficulty Level and Person Proficiency on Learning and Motivation
Systems 2016, 4(1), 14; doi:10.3390/systems4010014
Received: 24 September 2015 / Revised: 19 February 2016 / Accepted: 22 February 2016 / Published: 3 March 2016
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Abstract
The research on electronic learning environments has evolved towards creating adaptive learning environments. In this study, the focus is on adaptive curriculum sequencing, in particular, the efficacy of an adaptive curriculum sequencing algorithm based on matching the item difficulty level to the learner’s
[...] Read more.
The research on electronic learning environments has evolved towards creating adaptive learning environments. In this study, the focus is on adaptive curriculum sequencing, in particular, the efficacy of an adaptive curriculum sequencing algorithm based on matching the item difficulty level to the learner’s proficiency level. We therefore explored the effect of the relative difficulty level on learning outcome and motivation. Results indicate that, for learning environments consisting of questions focusing on just one dimension and with knowledge of correct response, it does not matter whether we present easy, moderate or difficult items or whether we present the items with a random mix of difficulty levels, regarding both learning and motivation. Full article
(This article belongs to the Special Issue Adaptive Educational Technology Systems)
Open AccessArticle Effective Presentation Speech Support System for Representing Emphasis-Intention
Systems 2016, 4(1), 1; doi:10.3390/systems4010001
Received: 29 September 2015 / Revised: 30 November 2015 / Accepted: 15 December 2015 / Published: 23 December 2015
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Abstract
A research presentation integrates slides and speech. If these two aspects do not represent the same intention, the presentation will probably fail to effectively explain the presenter’s intention. This paper focuses on the representation of the critical contents in a presentation. In an
[...] Read more.
A research presentation integrates slides and speech. If these two aspects do not represent the same intention, the presentation will probably fail to effectively explain the presenter’s intention. This paper focuses on the representation of the critical contents in a presentation. In an effective speech, the speaker adds more intonation and stress to emphasize the importance of the slide contents. Audiences recognize that important contents are those that are explained in a stronger voice or that are said after a short pause. However, in ineffective speeches, such voice effects do not always correspond to the important contents that are indicated by slides. On slides, the important contents are represented by levels of text indentation and size, color, and animation. This research develops a presentation speech support system that estimates important contents from slides and voices that might be recognized by audiences and extracts numerical differences. In addition, the system provides comments and feedback to improve speeches. Full article
(This article belongs to the Special Issue Adaptive Educational Technology Systems)
Open AccessArticle Supporting Student Learning in Computer Science Education via the Adaptive Learning Environment ALMA
Systems 2015, 3(4), 237-263; doi:10.3390/systems3040237
Received: 9 June 2015 / Revised: 26 September 2015 / Accepted: 30 September 2015 / Published: 12 October 2015
PDF Full-text (782 KB) | HTML Full-text | XML Full-text
Abstract
This study presents the ALMA environment (Adaptive Learning Models from texts and Activities). ALMA supports the processes of learning and assessment via: (1) texts differing in local and global cohesion for students with low, medium, and high background knowledge; (2) activities corresponding to
[...] Read more.
This study presents the ALMA environment (Adaptive Learning Models from texts and Activities). ALMA supports the processes of learning and assessment via: (1) texts differing in local and global cohesion for students with low, medium, and high background knowledge; (2) activities corresponding to different levels of comprehension which prompt the student to practically implement different text-reading strategies, with the recommended activity sequence adapted to the student’s learning style; (3) an overall framework for informing, guiding, and supporting students in performing the activities; and; (4) individualized support and guidance according to student specific characteristics. ALMA also, supports students in distance learning or in blended learning in which students are submitted to face-to-face learning supported by computer technology. The adaptive techniques provided via ALMA are: (a) adaptive presentation and (b) adaptive navigation. Digital learning material, in accordance with the text comprehension model described by Kintsch, was introduced into the ALMA environment. This material can be exploited in either distance or blended learning. Full article
(This article belongs to the Special Issue Adaptive Educational Technology Systems)

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