3,121 research outputs found
Using adaptive hypermedia to support diversity in secondary schools
Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. F. Muñoz, and A. Ortigosa, âUsing adaptive hypermedia to support diversity in secondary schoolsâ, in Sixth International Conference on Advanced Learning Technologies, 2006, Kerkrade, 2006, pp. 1055-1059Attention to diversity is growing concern in public secondary schools in Spain. This paper presents an assessment about the use of adaptive hypermedia technology for supporting diversity. Three experiences were carried out with an adaptive course on mathematics to test the effects of this technology on the heterogeneous population of secondary schools. Their results and conclusions are also presentedThis work has been funded by the Spanish Ministry of Science and Education, TIN2004-03140
Responsible research and innovation in science education: insights from evaluating the impact of using digital media and arts-based methods on RRI values
The European Commission policy approach of Responsible Research and Innovation (RRI) is gaining momentum in European research planning and development as a strategy to align scientific and technological progress with socially desirable and acceptable ends. One of the RRI agendas is science education, aiming to foster future generations' acquisition of skills and values needed to engage in society responsibly. To this end, it is argued that RRI-based science education can benefit from more interdisciplinary methods such as those based on arts and digital technologies. However, the evidence existing on the impact of science education activities using digital media and arts-based methods on RRI values remains underexplored. This article comparatively reviews previous evidence on the evaluation of these activities, from primary to higher education, to examine whether and how RRI-related learning outcomes are evaluated and how these activities impact on students' learning. Forty academic publications were selected and its content analysed according to five RRI values: creative and critical thinking, engagement, inclusiveness, gender equality and integration of ethical issues. When evaluating the impact of digital and arts-based methods in science education activities, creative and critical thinking, engagement and partly inclusiveness are the RRI values mainly addressed. In contrast, gender equality and ethics integration are neglected. Digital-based methods seem to be more focused on students' questioning and inquiry skills, whereas those using arts often examine imagination, curiosity and autonomy. Differences in the evaluation focus between studies on digital media and those on arts partly explain differences in their impact on RRI values, but also result in non-documented outcomes and undermine their potential. Further developments in interdisciplinary approaches to science education following the RRI policy agenda should reinforce the design of the activities as well as procedural aspects of the evaluation research
The role of unit evaluation, learning and culture dimensions related to student cognitive style in hypermedia learning
Recent developments in learning technologies such as hypermedia are\ud
becoming widespread and offer significant contributions to improving the delivery\ud
of learning and teaching materials. A key factor in the development of hypermedia\ud
learning systems is cognitive style (CS) as it relates to usersâ information\ud
processing habits, representing individual usersâ typical modes of perceiving,\ud
thinking, remembering and problem solving.\ud
\ud
\ud
\ud
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A total of 97 students from Australian (45) and Malaysian (52) universities\ud
participated in a survey. Five types of predictor variables were investigated with\ud
the CS: (i) three learning dimensions; (ii) five culture dimensions; (iii) evaluation\ud
of units; (iv) demographics of students; and (v) country in which students studied.\ud
Both multiple regression models and tree-based regression were used to analyse\ud
the direct effect of the five types of predictor variables, and the interactions within\ud
each type of predictor variable. When comparing both models, tree-based\ud
regression outperformed the generalized linear model in this study. The research\ud
findings indicate that unit evaluation is the primary variable to determine studentsâ\ud
CS. A secondary variable is learning dimension and, among the three dimensions,\ud
only nonlinear learning and learner control dimensions have an effect on studentsâ\ud
CS. The last variable is culture and, among the five culture dimensions, only\ud
power distance, long term orientation, and individualism have effects on studentsâ\ud
CS. Neither demographics nor country have an effect on studentsâ CS.\ud
These overall findings suggest that traditional unit evaluation, studentsâ\ud
preference for learning dimensions (such as linear vs non-linear), level of learner\ud
control and culture orientation must be taken into consideration in order to enrich\ud
studentsâ quality of education. This enrichment includes motivating students to\ud
acquire subject matter through individualized instruction when designing,\ud
developing and delivering educational resources
Evaluating Digital Libraries: A Longitudinal and Multifaceted View
published or submitted for publicatio
An Adaptive E-Learning System based on Studentâs Learning Styles and Knowledge Level
Es besteht eine starke Nachfrage nach einer positiven Applikation zum Lernen, um den strategischen Plan des indonesischen Ministeriums fĂŒr Bildung und Kultur zu fördern, dass die Ratio von Berufsschule höher als die allgemeinbildende Schule werden kann. Die rasante entwicklung der Informations- und Kommunikationstechnologie könnte es ermöglichen, den Lernenden ein computergestĂŒtztes, personalisiertes E-Learning-System zur VerfĂŒgung zu stellen, um die Tatsache zu ĂŒberwinden, dass jeder Lernende seine eigene PrĂ€ferenz hat. Diese Studie bietet ein adaptives E-Learning-System, bei dem zwei Quellen der Personalisierung berĂŒcksichtigt werden: der Lernstil des SchĂŒlers und das Vorwissen. Um die Wirksamkeit des vorgeschlagenen E-Learning-Programms zu untersuchen, werden die Leistungen der SchĂŒler bezĂŒglich der drei niedrigsten Ebenen im kognitiven Bereich (Wissen, VerstĂ€ndnis und Anwendung) in der E-Learning-Gruppe mit denen der traditionellen Unterrichtsgruppe verglichen. Ein weiterer interessanter Bereich ist die sogannte schĂŒlerperspektive Usability-Bewertung und die Beziehung zwischen den Usability-Fragebogen angegebenen Aspekten zu erforschen.
Der Entwurfs- und Entwicklungsprozess des adaptiven E-Learning-Systems in dieser Studie berĂŒcksichtigte sowohl das Instruktionsdesign als auch das Software-Engineering. Die erste Phase begann mit der Analyse des Kandidaten der Teilnehmer, des Fachkurses und des Online-Liefermediums. Der nĂ€chste Schritt bestand darin, die Prozedur, die Regelwerk der Adaptation und die BenutzeroberflĂ€che zu entwerfen. Dann wurde Entwicklungsprozess des Lehrsystems auf der Grundlage der aus den vorherigen Phasen gesammelten Daten durchgefĂŒhrt. Die nĂ€chste Phase war die Implementierung des Unterrichtsprogramms fĂŒr die SchĂŒler in einer kleinen Gruppe. SchlieĂlich wurde die E-Learning-Anwendung in drei verschiedenen Teststrategien bewertet: Funktionsbasiertes Testen, Expertenbasierte Bewertung und benutzerperspektivische Bewertung.
Die nĂ€chste Aktion ist eine experimentelle Studie, bei der das adaptive E-Learning-System im Lernprozess angewendet wird. An diesem Experiment waren zwei Gruppen beteiligt. Die Experimentalgruppe bestand aus 21 Studenten, die den Unterrichtsfach Digital Simulation mithilfe des adaptiven E-Learning-Systems lernten. Eine andere Gruppe war die Kontrollgruppe, die 21 SchĂŒler umfasste, die dasselbe Unterrichtsfach in der traditionellen Klasse lernten. Es wurden zwei Instrumente verwendet, um die erforderlichen Daten zu erheben. Das erste Instrument bestand aus 30 Multiple-Choice-Fragen, die die kognitiven Ebenen von Wissen, Verstehen und Anwendung enthielten. Dieses Instrument wurde verwendet, um die SchĂŒlerleistung bei dem obengeschriebenen Unterrichtsfach zu bewerten. Das zweite Instrument war der Usability-Fragebogen, der aus 30 4-Punkte-Likert Aussagen bestand. Dieser Fragebogen bestand aus vier Dimensionen nĂ€mlich NĂŒtzlichkeit, Benutzerfreundlichkeit, Lernfreundlichkeit und Zufriedenheit. Mit diesem Fragebogen wurde die Usability der adaptiven E-Learning-Applikation basierend auf die Perspektive des SchĂŒlers bewertet.
Der Befund dieser Studie ergab ein ungewöhnliches PhĂ€nomen, bei dem das Ergebnis des Pre-Tests der Kontrollgruppe signifikant höher als Experimentalgruppe. Zum Post-Test Vergleich, obwohl die Leistung der E-Learning Gruppe höher als der von der regulĂ€ren war, war der Unterschied zwischen den beiden statistisch nicht signifikant. Der Vergleich der Punktzahlsteigerung wurde gemacht, um zu untersuchen, welche Behandlungsgruppe effektiver war. Die Ergebnisse zeigten, dass die gesamte Punktzahlsteigerung von der Experimentalgruppe signifikant höher als die von der Kontrollgruppe war. Diese Beweise waren auch im Hinblick auf das Wissen, das VerstĂ€ndnis und die Anwendungsebene des kognitiven Bereichs gĂŒltig. Diese Ergebnisse bestĂ€tigten, dass die Gruppe des adaptiven E-Learning-Systems bezĂŒglich ihrer Leistung effektiver war als die Gruppe der Studenten, die in der traditionellen Klasse lernten. Ein weiterer wichtiger Befund betraf die Bewertung der Usability. Die Punktzahl der Messung wurde anhand verschiedener AnsĂ€tze analysiert und ergab, dass der Usability-Score in allen Aspekten (NĂŒtzlichkeit, Benutzerfreundlichkeit, Lernfreundlichkeit und Zufriedenheit) den akzeptablen Kriterien zuzuordnen ist. DarĂŒber hinaus wurde die Regressionsanalyse durchgefĂŒhrt, um die Beziehung zwischen den Variablen zu untersuchen. Der erste Befund ergab, dass die unabhĂ€ngigen Variablen (NĂŒtzlichkeit, Benutzerfreundlichkeit und Lernfreundlichkeit) gleichzeitig die abhĂ€ngige Variable (Zufriedenheit) beeinflussten. In der Zwischenzeit ergab der Teil t-Test unterschiedliche Ergebnisse. Die Ergebnisse zeigten, dass die variable Benutzerfreundlichkeit die variable Zufriedenheit signifikant beeinflusste. Der variable NĂŒtzlichkeit und die Lernfreundlichkeit wirkten sich indessen nicht signifikant auf die variable Zufriedenheit aus.There is a strong demand for a positive instructional application in order to address the strategic plan of the Ministry of Education and Culture in Indonesia to change the ratio of vocational secondary school to be higher than the general school one. The immense growth of information and communication technology may be possible to provide a computer-based personalized e-learning system to the learners in order to overcome the fact that each student has their own preferences in learning. This study offers an adaptive e-learning system by considering two sources of personalization: the studentâs learning style and initial knowledge. In order to investigate the effectiveness of the proposed e-learning program, the studentsâ achievement in terms of three lowest levels in the cognitive domain (knowledge, comprehension, and application) in the e-learning group is compared with the traditional classroom group. Another area that is interesting to explore is the usability evaluation based on the studentsâ perspective and the relationship between aspects specified in the usability questionnaire.
The design and development process of the adaptive e-learning system in this study was considering both the instructional system design and software engineering. The first phase was started by analyzing the participantsâ candidate, the subject course, and the online delivery medium. The next step was designing the procedure, the adaptation set of rules, and the user interface. Then, the process to develop the instructional system based on the data collected from the previous phases was conducted. The next stage was implemented the instructional program to the students in a small group setting. Finally, the e-learning application was evaluated in three different settings: functional-based testing, experts-based assessment, and user-perspective evaluation.
The next action is an experimental study by applying the adaptive e-learning system to the learning process. There were two groups involved in this experiment. The experimental group that consisted of 21 students who learned the Digital Simulation course by utilizing the adaptive e-learning system. Another group was the control group that included 21 students who studied the same course through the traditional classroom setting. There were two instruments used to collect the required data. The first instrument contained 30 multiple-choice questions that considered the cognitive levels of knowledge, comprehension, and application. This instrument was used to assess the student achievement of the intended course. The second instrument was the usability questionnaire that consisted of 30 4-point Likert scale statements. This questionnaire was composed of four dimensions, namely usefulness, ease of use, ease of learning, and satisfaction. This questionnaire aimed to evaluate the usability of the adaptive e-learning application based on the studentâs perspective.
The finding in this study revealed an unusual phenomenon which the pre-test result of the control group was significantly exceeding those of the experimental group. For the post-test score comparison, although there was a higher achievement in the e-learning group than in the regular group, the difference between both achievements was not statistically significant. The comparison in terms of the gain score was conducted in order to investigate which treatment group was more effective. The results indicated that the total gain score achieved by the experimental group was significantly higher than those recorded by the control group. This evidence was also valid with regard to the knowledge, comprehension, and application-level of the cognitive domain. These findings confirmed that the group who utilized the adaptive e-learning system was reported more effective in terms of the achievement score than the group of students who studied in the traditional setting. Another important finding was related to usability evaluation. The measurement score was analyzed through different approaches and revealed that the usability score categorized in the acceptable criteria in all aspects (usefulness, ease of use, ease of learning, and satisfaction). Furthermore, the regression analysis was conducted in order to explore the relation between the variables. The first finding reported that the independent variables (usefulness, ease of use, and ease of learning) simultaneously influenced the dependent variable (satisfaction). In the meantime, the partial t-Test found varying results. The results indicated that the variable ease of use was significantly influenced variable satisfaction. Meanwhile, variable usefulness and ease of learning were not significantly affected variable satisfaction
Using decision trees for discovering problems on adaptive courses
Copyright by AACE. Reprinted from the World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, Nov 17, 2008, with permission of AACE (http://www.aace.org).Adaptive Hypermedia Systems personalize the learning experience of each user, by providing learning materials adapted to his/her needs, preferences, personal characteristics, etc. The goal is to make the learning process easier or more efficient. However, on the teacher side the improvement and evaluation of these systems are difficult tasks, especially when there are multiple student profiles or huge amount of interaction data of students. In this work, data mining methods, and specifically decision trees, are used for helping in both improvement and evaluation. Our work consists of analyzing two data sets by using decision trees. The first data set contains the interaction data of 24 real students, and the second data set is composed of synthetic data about 100 students. The results of these analyses demonstrated that 24 students is a small data set when decision trees are used. However, the tree showed information relating to the practical activities in which students had more problems for completing them providing useful feedback to the course designer.This work has been funded by Spanish Ministry of Science and Education through the HADA project TIN2007-64718. Cesar Vialardi is also funded by FundaciĂłn Carolina
USE SOCIAL NETWORK ANALYSIS TO IDENTIFY THE KNOWLEDGE-HOLE FROM LEARNING PORTFOLIOS STRUCTURES THROUGH WEB LOGS IN COGNITIVE APPRENTICESHIP AND GOAL-BASED WEB-BASED LEARNING SYSTEM
This paper presented an in-progress research model to develop, design and test an innovated acculturated adaptive web-based learning systems which based on Vygotsky ïŒs zone of proximal development (ZPD) development theory. Based on ZPD related theories and researches, this research proposed to use cognitive apprenticeship instruction model as design guides to develop the activity functions to support acculturation ZPD instructions in MOODLE, a most popular opensource web-based learning system in the world. A support acculturation ZPD instruction adaptive system engine/mechanism, Heuristic Adaptive Learning Pattern (HALP), were also proposed in this paper. The major proposed designed adaptive function will base on the Blockmodeling method that used in social network analysis methodology which modelling the learnerâs learning portfolio and learning path
Dimensions of personalisation in technology-enhanced learning: a framework and implications for design
Personalisation of learning is a recurring trend in our society, referred to in government speeches, popular media, conference and research papers and technological innovations. This latter aspectâof using personalisation in technology-enhanced learning (TEL)âhas promised much but has not always lived up to the claims made. Personalisation is often perceived to be a positive phenomenon, but it is often difficult to know how to implement it effectively within educational technology.
In order to address this problem, we propose a framework for the analysis and creation of personalised TEL. This article outlines and explains this framework with examples from a series of case studies. The framework serves as a valuable resource in order to change or consolidate existing practice and suggests design guidelines for effective implementations of future personalised TEL
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