Oldenburg, Universiẗat, Diss., 2003.

Marburg, Universiẗat, Diss., 2008.

Zugl.: Göttingen, Universiẗat, Diss., 2009.

Zugl.: Marburg, Univ., Diss., 1992 u.d.T.: Schrader, Josef: Lernstile in der beruflichen Weiterbildung / 1. Aufl. im Dt. Studien-Verl., Weinheim

Zugl.: Hamburg, Univ., Diss., 2008

The study was aimed at revealing (1) how the instructional media of industrial electronics integrated with learning style instrument was developed, (2) the feasibility of the instructional media of industrial electronics integrated with the learning style instruments, (3) the effect of the instructional media on learning achievement, and (4) the effect of the instructional media on learning satisfaction. The study employed the Design and Development Research (DDR) model. The development procedure used the Specific Project Phases Cluster, consisting of (1) analysis, (2) design, (3) development, and (4) evaluation. The preliminary research was carried out as a part of the analysis phase. The analysis phase started with a survey of lecturers/teachers and vocational high school teachers as respondents. The prototype of the product was tested by subject matter, software, and media experts related to the teaching media as a whole, and through a small group field test among a number of students. The data were collected through questionnaires in the form of Likert scale and were analyzed descriptively quantitatively. The results of the study showed (1) the instructional media was developed through the design and development research (DDR) model with the Design & Development Tools cluster which served as a part of the Product and Tool research main cluster, (2) the instructional media was feasible to use without revision, (3) the study showed a t-value of -6.999, df = 21, and p-value of 0.000, since p < 0.01, there was a statistically significant difference in the learning achievement before and after the use of the instructional media, with the effect size of d=1.49 (d>0.8), so the effect of the media was categorized to have a large effect, and (4) the instructional media could bring positive effects on the learning satisfaction. It is shown that the aspect of material was categorized into good (81.6%), the aspect of presentation was categorized into good (76.3%), the aspect of ease and satisfaction in using the learning software was also good (65.8% and 57.9%) and the learning media as a whole was categorized into good (76.3%).:ABSTRAK i ABSTRACT ii CHAPTER I 1 INTRODUCTION 1 CHAPTER II 13 LITERATURE REVIEW 13 CHAPTER THREE 57 RESEARCH METHOD 57 CHAPTER FOUR 89 RESEARCH FINDING 89 CHAPTER FIVE 186 CONCLUSIONS AND RECOMMENDATIONS 186 A. CONCLUSIONS 186 B. RECOMMENDATION 188 C. DISSEMINATION AND FUTURE PRODUCT DEVELOPMENT 189 REFERENCES 190 APPENDICES 198

Learning style preferences play a significant role during the learning and teaching process. Therefore, a multitude of researchers have developed different models to accommodate students’ various learning styles. Those models share the same goal of trying to classify a particular students’ learning style and to provide an overview of better teaching strategies for educators. This paper presents a research study based on a survey that investigates the learning style preferences of computer network vocational senior secondary school students in Yogyakarta Province, Indonesia. This survey uses the Index of Learning Styles (ILS) questionnaire developed by Felder and Solomon. In total, 162 data sets from five different schools in five different areas were collected in order to represent the Yogyakarta Province. The findings from the study show that students participating in computer network vocational training preferred active (82.66%), sensing (67.66%), visual (83.83%), and sequential (52.44%) learning styles. Students most strongly prefer visual and least favor verbal (16.17%). Identifying learning styles can benefit teachers as they customize teaching methods and can maximize the learning and teaching process.

Es besteht eine starke Nachfrage nach einer positiven Applikation zum Lernen, um den strategischen Plan des indonesischen Ministeriums für 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 computergestütztes, personalisiertes E-Learning-System zur Verfügung zu stellen, um die Tatsache zu überwinden, dass jeder Lernende seine eigene Präferenz hat. Diese Studie bietet ein adaptives E-Learning-System, bei dem zwei Quellen der Personalisierung berücksichtigt werden: der Lernstil des Schülers und das Vorwissen. Um die Wirksamkeit des vorgeschlagenen E-Learning-Programms zu untersuchen, werden die Leistungen der Schüler bezüglich der drei niedrigsten Ebenen im kognitiven Bereich (Wissen, Verständnis und Anwendung) in der E-Learning-Gruppe mit denen der traditionellen Unterrichtsgruppe verglichen. Ein weiterer interessanter Bereich ist die sogannte schülerperspektive 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 berücksichtigte 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 nächste Schritt bestand darin, die Prozedur, die Regelwerk der Adaptation und die Benutzeroberfläche zu entwerfen. Dann wurde Entwicklungsprozess des Lehrsystems auf der Grundlage der aus den vorherigen Phasen gesammelten Daten durchgeführt. Die nächste Phase war die Implementierung des Unterrichtsprogramms für die Schüler in einer kleinen Gruppe. Schließlich wurde die E-Learning-Anwendung in drei verschiedenen Teststrategien bewertet: Funktionsbasiertes Testen, Expertenbasierte Bewertung und benutzerperspektivische Bewertung. Die nächste 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 Schüler 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 Schülerleistung 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 nämlich Nützlichkeit, Benutzerfreundlichkeit, Lernfreundlichkeit und Zufriedenheit. Mit diesem Fragebogen wurde die Usability der adaptiven E-Learning-Applikation basierend auf die Perspektive des Schülers bewertet. Der Befund dieser Studie ergab ein ungewöhnliches Phänomen, 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 regulären 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 Verständnis und die Anwendungsebene des kognitiven Bereichs gültig. Diese Ergebnisse bestätigten, dass die Gruppe des adaptiven E-Learning-Systems bezüglich 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 Ansätze analysiert und ergab, dass der Usability-Score in allen Aspekten (Nützlichkeit, Benutzerfreundlichkeit, Lernfreundlichkeit und Zufriedenheit) den akzeptablen Kriterien zuzuordnen ist. Darüber hinaus wurde die Regressionsanalyse durchgeführt, um die Beziehung zwischen den Variablen zu untersuchen. Der erste Befund ergab, dass die unabhängigen Variablen (Nützlichkeit, Benutzerfreundlichkeit und Lernfreundlichkeit) gleichzeitig die abhängige 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 Nützlichkeit 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 student’s learning style and initial knowledge. In order to investigate the effectiveness of the proposed e-learning program, the students’ 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 students’ 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 participants’ 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 student’s 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.

Learning style preferences play a significant role during the learning and teaching process. Therefore, a multitude of researchers have developed different models to accommodate students’ various learning styles. Those models share the same goal of trying to classify a particular students’ learning style and to provide an overview of better teaching strategies for educators. This paper presents a research study based on a survey that investigates the learning style preferences of computer network vocational senior secondary school students in Yogyakarta Province, Indonesia. This survey uses the Index of Learning Styles (ILS) questionnaire developed by Felder and Solomon. In total, 162 data sets from five different schools in five different areas were collected in order to represent the Yogyakarta Province. The findings from the study show that students participating in computer network vocational training preferred active (82.66%), sensing (67.66%), visual (83.83%), and sequential (52.44%) learning styles. Students most strongly prefer visual and least favor verbal (16.17%). Identifying learning styles can benefit teachers as they customize teaching methods and can maximize the learning and teaching process.