Τα σύγχρονα πληροφοριακά συστήματα μάθησης τα οποία υποστηρίζουν εξ’ αποστάσεως εκπαίδευση, επιτρέπουν τη συστηματική διαχείριση του εκπαιδευτικού υλικού και υποστηρίζουν τις εκπαιδευτικές διαδικασίες των μαθημάτων. Τα συστήματα αυτά έχουν λειτουργικότητες όπως: η ανάρτηση ψηφιακού υλικού, η διεξαγωγή συζητήσεων, η ανάρτηση ασκήσεων-εργασιών, η πραγματοποίηση εξετάσεων και πολλές άλλες. Στόχος της συγκεκριμένης εργασίας είναι η διερεύνηση του χώρου των συστημάτων μάθησης τα οποία υποστηρίζουν εξ’ αποστάσεως εκπαίδευση καθώς επίσης και η παρουσίαση και η εφαρμογή μεθόδου αξιολόγησης τους, αξιολογώντας τα συστήματα σύμφωνα με μια λίστα λειτουργικών απαιτήσεων. Στο 1ο κεφάλαιο της διπλωματικής εργασίας γίνεται μια περιγραφή των βασικών εννοιών της εξ’αποστάσεως εκπαίδευσης καθώς επίσης και έννοιες που αφορούν τα συστήματα υποστήριξης μάθησης όπως:CBT, VLE, LMS, LCMS, CMS, Mobile Learning. Στο 2ο κεφάλαιο γίνεται μια επισκόπηση του χώρου των Συστημάτων Μάθησης Learning Course Management Systems (LCMS). Συγκεκριμένα γίνεται μία καταγραφή των χαρακτηριστικών των πιο δημοφιλών συστημάτων τόσο των εμπορικών όσο και των συστημάτων ανοικτού κώδικα με τη χρήση ενός κοινού template όπου καταγράφονται τα εξής στοιχεία: Κατασκευαστής, Σύντομη περιγραφή Λογισμικού, Πλεονεκτήματα (Δυνατά Σημεία ), Μειονεκτήματα (Αδυναμίες, Ελλείψεις), Πελατολόγιο, Τρέχουσα Έκδοση έτσι ώστε να μπορεί κάποιος εύκολα να τα συγκρίνει και να τα αξιολογήσει. Στο 3ο κεφάλαιο πραγματοποιείται ανάλυση απαιτήσεων ενός σύγχρονου συστήματος μάθησης έτσι ώστε να μπορεί να εφαρμοστεί η μεθοδολογία αξιολόγησης σε μια λίστα από χαρακτηριστικά-απαιτήσεις για τα συστήματα που παρουσιάζονται στο κεφάλαιο 2. Στο 4ο κεφάλαιο παρουσιάζεται η μεθοδολογία Αξιολόγησης των συστημάτων μάθησης η οποία στηρίζεται στη θεωρία της ασαφούς λογικής. Η συγκεκριμένη μεθοδολογία εφαρμόστηκε σαν μελέτη περίπτωσης για την αξιολόγηση συστημάτων εκπαιδευτικών δραστηριοτήτων προκειμένου να βρεθεί το πλέον κατάλληλο σύστημα για τις ανάγκες του Ελληνικού Ανοικτού Πανεπιστημίου. Τέλος στο κεφάλαιο 5 πραγματοποιείται η εφαρμογή της μεθοδολογίας αξιολόγησης μεταξύ των συστημάτων μάθησης και παρουσιάζονται τα αποτελέσματα- συμπεράσματα που εξάγονται από την εφαρμογή της μεθόδου ενώ στο τελευταίο κεφάλαιο (6ο ) παρουσιάζονται τα συμπεράσματα της εργασίας. / Modern learning information systems are designed to support distance education and have many features to support learning sequence such as: management of educational material, tools for uploading projects in several kinds (documents, multimedia files), many kinds of quizzes, grades management, forums, reports wiz and many others. The aim of this master thesis is the investigation of available learning course management systems(LCMS), requirements analysis for LCMS and presentation and implementation of an evaluation methodology for LCMS based on a requirements list. In the first chapter of this thesis, we describe the basic concepts and definitions of e-Learning, as well as concepts relating to learning support systems such as: CBT(Computer Based Training), VLE(Virtual Learning Environment), LMS(Learning Management Systems), LCMS(Learning Course Management Systems), CMS (Course Management Systems), Mobile Learning etc. The second chapter contains an investigation in the area of Learning Course Management Systems (LCMS). We used a common template in order to describe the features of the most popular LCMS (either Open Source or Commercial). The template contains features like: Small Description of any LCMS (Software Manufacturer and History, Active Users and Installations, Database Requirements, Web Server, Manufacturer Clients, Current Stable Version), Strengths of the Software, Weaknesses of the Software, Available Mobile Version. This features have been chosen in order to become easy the comparison and after that the evaluation of the systems. The third chapter contains requirements analysis of a modern learning course management system so that the evaluation methodology can be applied to a specified list of features-requirements for the systems presented in chapter 2. In the fourth chapter there is the presentation of the evaluation methodology which uses a multicriteria technical analysis which belongs to the field of methods of Multi-Criteria Group-based Decision Making Techniques, while uses methods of (intuitionistic) fuzzy logic. This method exports the results using a technique TOPSIS(Technique for Order Preference by Similarity to Ideal Solution). In this chapter there is the theoretical description of the methodology which has been implemented as a case study for evaluating learning management systems in order to find the most suitable system for the needs of the Hellenic Open University(HOU). In Chapter 5 we will find the implementation steps of the methodology in order to exclude the most suitable LCMS for HOU and the final results(list of Systems). We will also find the conclusions of the implementation of this method. Finally the last chapter (6th) presents the final conclusions of the whole thesis and the added value this thesis offers in this field of research .

The purpose of the study was to describe the effects of an EMR on patient management in selected HIV clinics in Johannesburg. A quantitative, descriptive, cross-sectional study was undertaken in four HIV clinics in Johannesburg. The subjects (N=44) were the healthcare workers selected by stratified random sampling. Consent was requested from each subject and from the clinics in Johannesburg. Data was collected using structured questionnaires. Median age of subjects was 36, 82% were female. 86% had tertiary qualifications. 55% were clinicians. 52% had 2-3 years work experience. 80% had computer experience, 86% had over one year EMR experience. 90% used the EMR daily, 93% preferred EMR to paper. 93% had EMR training, 17% used EMR to capture clinical data. 87% perceived EMR to have more benefits; most felt doctor-patient relationship was not interfered with. 89% were satisfied with the EMR’s overall performance. The effects of EMR benefit HIV patient management. / Health Studies / MA (Public Health)

Despite widespread recognition by science educators, researchers and K-12 frameworks that scientific inquiry should be an essential part of science education, typical classrooms and assessments still emphasize rote vocabulary, facts, and formulas. One of several reasons for this is that the rigorous assessment of complex inquiry skills is still in its infancy. Though progress has been made, there are still many challenges that hinder inquiry from being assessed in a meaningful, scalable, reliable and timely manner. To address some of these challenges and to realize the possibility of formative assessment of inquiry, we describe a novel approach for evaluating, tracking, and scaffolding inquiry process skills. These skills are demonstrated as students experiment with computer-based simulations. In this work, we focus on two skills related to data collection, designing controlled experiments and testing stated hypotheses. Central to this approach is the use and extension of techniques developed in the Intelligent Tutoring Systems and Educational Data Mining communities to handle the variety of ways in which students can demonstrate skills. To evaluate students' skills, we iteratively developed data-mined models (detectors) that can discern when students test their articulated hypotheses and design controlled experiments. To aggregate and track students' developing latent skill across activities, we use and extend the Bayesian Knowledge-Tracing framework (Corbett & Anderson, 1995). As part of this work, we directly address the scalability and reliability of these models' predictions because we tested how well they predict for student data not used to build them. When doing so, we found that these models demonstrate the potential to scale because they can correctly evaluate and track students' inquiry skills. The ability to evaluate students' inquiry also enables the system to provide automated, individualized feedback to students as they experiment. As part of this work, we also describe an approach to provide such scaffolding to students. We also tested the efficacy of these scaffolds by conducting a study to determine how scaffolding impacts acquisition and transfer of skill across science topics. When doing so, we found that students who received scaffolding versus students who did not were better able to acquire skills in the topic in which they practiced, and also transfer skills to a second topic when was scaffolding removed. Our overall findings suggest that computer-based simulations augmented with real-time feedback can be used to reliably measure the inquiry skills of interest and can help students learn how to demonstrate these skills. As such, our assessment approach and system as a whole shows promise as a way to formatively assess students' inquiry.

Despite widespread recognition by science educators, researchers and K-12 frameworks that scientific inquiry should be an essential part of science education, typical classrooms and assessments still emphasize rote vocabulary, facts, and formulas. One of several reasons for this is that the rigorous assessment of complex inquiry skills is still in its infancy. Though progress has been made, there are still many challenges that hinder inquiry from being assessed in a meaningful, scalable, reliable and timely manner. To address some of these challenges and to realize the possibility of formative assessment of inquiry, we describe a novel approach for evaluating, tracking, and scaffolding inquiry process skills. These skills are demonstrated as students experiment with computer-based simulations. In this work, we focus on two skills related to data collection, designing controlled experiments and testing stated hypotheses. Central to this approach is the use and extension of techniques developed in the Intelligent Tutoring Systems and Educational Data Mining communities to handle the variety of ways in which students can demonstrate skills. To evaluate students' skills, we iteratively developed data-mined models (detectors) that can discern when students test their articulated hypotheses and design controlled experiments. To aggregate and track students' developing latent skill across activities, we use and extend the Bayesian Knowledge-Tracing framework (Corbett & Anderson, 1995). As part of this work, we directly address the scalability and reliability of these models' predictions because we tested how well they predict for student data not used to build them. When doing so, we found that these models demonstrate the potential to scale because they can correctly evaluate and track students' inquiry skills. The ability to evaluate students' inquiry also enables the system to provide automated, individualized feedback to students as they experiment. As part of this work, we also describe an approach to provide such scaffolding to students. We also tested the efficacy of these scaffolds by conducting a study to determine how scaffolding impacts acquisition and transfer of skill across science topics. When doing so, we found that students who received scaffolding versus students who did not were better able to acquire skills in the topic in which they practiced, and also transfer skills to a second topic when was scaffolding removed. Our overall findings suggest that computer-based simulations augmented with real-time feedback can be used to reliably measure the inquiry skills of interest and can help students learn how to demonstrate these skills. As such, our assessment approach and system as a whole shows promise as a way to formatively assess students' inquiry.

Recent research has challenged the way in which personality and attitude constructs are measured. Alternatives have been offered as to how non-cognitive responses are modeled, the mode of delivery used when administrating such scales, and the impact of technology in measuring personality. Thus, the major purpose of the studies in this thesis concerns two interrelated issues of personality research, namely the way personality responses are best modeled, and the most optimal mode by which personality items are presented and associated modal issues. Three studies are presented. First, recent developments using an ideal point approach to scale construction are outlined, and an empirical study compares modeling personality items based on an ideal point approach (generalized graded unfolding model; GGUM) and a dominance approach (graded response model: GRM). Second, an extensive review of literature pertaining to the mode effect when transferring paper-and-pencil measures to screen was conducted, in addition to a review of the various types of computerized and innovative items and their associated psychometric information. Finally, nine innovative items were developed using various multimedia features (e.g., video, graphics, and audio) to ascertain the advantages of these methods to present items constructed to elicit response behavior underlying ideal point approaches, namely, typical response behavior. It was found that the dominance IRT model continued to produce superior model-data fit for most items, more attention needs to be placed on developing principles for constructing ideal point type items, the web-based version supplied 20% more construct information than the paper version, and innovative items seem to provide more data-model fit for students with lower personality attributes. While the innovative items may require more initial outlay in terms of time and development costs, they have the capacity to provide more information regarding test-takers’ personality levels, potentially using fewer items.

Die Bachelorarbeit dokumentiert die Entwicklung eines computerbasierten Lernangebots zum Thema „Gesundheitswesen in Deutschland“, welches als Untersuchungsmaterial in einer experimentellen Studie eingesetzt werden soll. Das Lernziel der Probanden ist, so viel wie möglich über Gesetze und Bestimmungen der Gesundheitsreform herauszufinden, um die Aufgabenbearbeitung und Lernzielerreichung erfolgreich zu absolvieren. Der erste Teil stellt die pädagogisch-psychologisch fundierte theoretische Konzeption eines computerbasierten Lernangebots dar. Dabei werden zunächst theoretische Grundlagen zum E-Learning, Instruktionsdesign, selbstgesteuerten Lernen und unterstützenden Lernaktivitäten gelegt. Danach erfolgt die Vorstellung von Lern- und Testaufgaben als eine Möglichkeit der Selbstregulation. Dabei wird besonders auf die formalen Aspekte von Aufgaben, das Generieren von Lehrzielen sowie die Konstruktion von fehlerbasiertem Feedback eingegangen. Im zweiten Teil erfolgt die darauf aufbauende praktische Umsetzung: Auf Basis des konzipierten Instruktionsdesigns erfolgt die Erarbeitung von Lernaktivitäten, welche von den Versuchspersonen zur Selbststeuerung ihrer Lernprozesse genutzt werden können. Dafür werden insbesondere Lernaufgaben zur fakultativen selbstständigen Wissensüberprüfung sowie Testaufgaben zur Erfassung des Wissenszuwachses konstruiert. Im Anhang sind die zum Thema „Gesundheitswesen in Deutschland“ entwickelten Lehrziele, konstruierten Aufgaben und dazugehöriges Feedback enthalten.

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Recent research has challenged the way in which personality and attitude constructs are measured. Alternatives have been offered as to how non-cognitive responses are modeled, the mode of delivery used when administrating such scales, and the impact of technology in measuring personality. Thus, the major purpose of the studies in this thesis concerns two interrelated issues of personality research, namely the way personality responses are best modeled, and the most optimal mode by which personality items are presented and associated modal issues. Three studies are presented. First, recent developments using an ideal point approach to scale construction are outlined, and an empirical study compares modeling personality items based on an ideal point approach (generalized graded unfolding model; GGUM) and a dominance approach (graded response model: GRM). Second, an extensive review of literature pertaining to the mode effect when transferring paper-and-pencil measures to screen was conducted, in addition to a review of the various types of computerized and innovative items and their associated psychometric information. Finally, nine innovative items were developed using various multimedia features (e.g., video, graphics, and audio) to ascertain the advantages of these methods to present items constructed to elicit response behavior underlying ideal point approaches, namely, typical response behavior. It was found that the dominance IRT model continued to produce superior model-data fit for most items, more attention needs to be placed on developing principles for constructing ideal point type items, the web-based version supplied 20% more construct information than the paper version, and innovative items seem to provide more data-model fit for students with lower personality attributes. While the innovative items may require more initial outlay in terms of time and development costs, they have the capacity to provide more information regarding test-takers’ personality levels, potentially using fewer items.

Recent research has challenged the way in which personality and attitude constructs are measured. Alternatives have been offered as to how non-cognitive responses are modeled, the mode of delivery used when administrating such scales, and the impact of technology in measuring personality. Thus, the major purpose of the studies in this thesis concerns two interrelated issues of personality research, namely the way personality responses are best modeled, and the most optimal mode by which personality items are presented and associated modal issues. Three studies are presented. First, recent developments using an ideal point approach to scale construction are outlined, and an empirical study compares modeling personality items based on an ideal point approach (generalized graded unfolding model; GGUM) and a dominance approach (graded response model: GRM). Second, an extensive review of literature pertaining to the mode effect when transferring paper-and-pencil measures to screen was conducted, in addition to a review of the various types of computerized and innovative items and their associated psychometric information. Finally, nine innovative items were developed using various multimedia features (e.g., video, graphics, and audio) to ascertain the advantages of these methods to present items constructed to elicit response behavior underlying ideal point approaches, namely, typical response behavior. It was found that the dominance IRT model continued to produce superior model-data fit for most items, more attention needs to be placed on developing principles for constructing ideal point type items, the web-based version supplied 20% more construct information than the paper version, and innovative items seem to provide more data-model fit for students with lower personality attributes. While the innovative items may require more initial outlay in terms of time and development costs, they have the capacity to provide more information regarding test-takers’ personality levels, potentially using fewer items.

Recent research has challenged the way in which personality and attitude constructs are measured. Alternatives have been offered as to how non-cognitive responses are modeled, the mode of delivery used when administrating such scales, and the impact of technology in measuring personality. Thus, the major purpose of the studies in this thesis concerns two interrelated issues of personality research, namely the way personality responses are best modeled, and the most optimal mode by which personality items are presented and associated modal issues. Three studies are presented. First, recent developments using an ideal point approach to scale construction are outlined, and an empirical study compares modeling personality items based on an ideal point approach (generalized graded unfolding model; GGUM) and a dominance approach (graded response model: GRM). Second, an extensive review of literature pertaining to the mode effect when transferring paper-and-pencil measures to screen was conducted, in addition to a review of the various types of computerized and innovative items and their associated psychometric information. Finally, nine innovative items were developed using various multimedia features (e.g., video, graphics, and audio) to ascertain the advantages of these methods to present items constructed to elicit response behavior underlying ideal point approaches, namely, typical response behavior. It was found that the dominance IRT model continued to produce superior model-data fit for most items, more attention needs to be placed on developing principles for constructing ideal point type items, the web-based version supplied 20% more construct information than the paper version, and innovative items seem to provide more data-model fit for students with lower personality attributes. While the innovative items may require more initial outlay in terms of time and development costs, they have the capacity to provide more information regarding test-takers’ personality levels, potentially using fewer items.