Thesis (M.Ed. (Educational Psychology))--University of the Witwatersrand, Faculty of Education, 1998.

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Large class size as a growing phenomenon in developing countries is closely related to two reasons: initiatives to achieve universal education and rapid population growth (Bendow, Mizrachi, Oliver, & Said-Moshiro, 2007; Shehu & Tafida, 2016). Given the fact that the large class phenomenon cannot be eliminated within a reasonable amount of time, it is important for teachers to develop effective strategies to teach English in large classes (Hayes, 1997). The purpose of this study was to understand in what ways post-observation discussions lead to increased self-awareness by a College English teacher of her pedagogy, especially related to large class teaching, and to provide insights which might be useful to teachers who teach large classes in China and around the world. The research site for this study was a four-year college in northern China. Data were collected from document analysis, observations, and discussions to answer the research questions. The post-observation discussions were structured by using the theoretical frameworks of the Cooperative Development model and a “collaborative conversation” approach. From a series of data analysis, four themes were generated from the data which included student participation, affective factors, classroom management, and instructional strategies. This study also provided implications of the findings and recommendations for further research.

Tertiary institutions in South Africa are currently faced with several challenges: Student numbers are increasing, funding is not necessarily sufficient and the type of student who enters Higher Education is part of a generation which grew up with technology (Prensky, 2001). Expectations are that tertiary education institutions need to keep up with the changing environment, whilst still maintaining high standards. Interaction within the learning environment is essential, both from an academic, as well as a social point of view. Students who leave the institution need to be able to function in a working environment, with all the challenges that accompany it, as well as be academically qualified for their careers. Universities, and specifically Economics departments, are often accused of being ivory towers with no regard for the real world (Fullbrook, 2003). The design for this study is a case-study within a qualitative research design. The study focuses on the use of an LMS to aid the learning process in a blended learning environment at the department of Economics, at the University of the Free State. In this study, several tools were used to support students and add another dimension to learning economics. Data-collection instruments include a literature review, focus group meetings, semi-structured questionnaires and observations. The value of this study is that it forms a basis for lecturers in other disciplines to include aspects of blended learning in their courses. The findings of the research include the usability of the different LMS tools, students’ experiences of these tools and the effect that these tools have on their understanding and integration of economics. The rationale of this study is based on the fact that students who attend university come from a generation identified as Digital Natives (Prensy, 2001) and have certain methods of data integration. The purpose of this study is, therefore, to focus and analyse students’ experiences of using WebCT tools as an additional aid to the course. The target group for the study was the Economics firstyear, second semester, English medium of instruction students. The course runs over a full semester, with two traditional facetoface classes, as well as tutor groups. In addition to two semester tests and an examination, students had to participate in a biweekly discussion forum, based on economic events and four online, multiple choice quizzes. They also had access to class notes, additional readings, informal discussions and a forum for questions. This research makes use of a qualitative approach and a casestudy, because it studies a “…human activity embedded in the real world which can only be studied or understood in context … which exists in the here and now that merges in with its context so that precise boundaries are difficult to draw” Gillham (2000). This study falls within the Interpretivist paradigm (Burrel and Morgan). Data were collected by means of focus group meetings, informal discussions, openended questionnaires, observations and a course evaluation. In this way, students’ attitudes towards the LMS could be gauged. Three categories were identified during the data analysis and coding process. The first category relates to interaction between students and lecturers (or tutors), the second to peerinteraction and the last category refers to contentstudent interaction. The findings of this study concludes that students need interaction with lecturers, peers and content in order to make sense of what they are learning, to link the theory with realworld issues and to enhance generic skills. Lecturers should consider making use of a hybrid learning system, but must consider their specific course content before deciding which of the available tools to use. / Thesis (PhD (Curriculum Studies))--University of Pretoria, 2006. / Curriculum Studies / unrestricted

Die Erforschung der Zusammenstellung kleiner Lerngruppen beschäftigt sich mit dem Problem, eine passende Gruppenzusammensetzung in einer Population von Lernern zu finden, die jeder Gruppe optimalen Nutzen bringen könnte. In letzter Zeit sind viele Studien zu diesem Problem der Kleingruppenzusammenstellung durchgeführt worden. Allerdings waren diese Forschungen nur selten auf den Kontext großer Lerner-Populationen ausgerichtet. Angesichts des zunehmenden Aufkommens von MOOCs muss jedoch das Problem der Gruppenzusammenstellung entsprechend erweitert betrachtet werden, und zwar mit neuen Forschungen, die den Kontext derartig großer Lerner-Populationen berücksichtigen. Anders als in Klassenzimmer-Settings könnte die beobachtete hohe Abbruchquote in MOOCs in einer Unterbesetzung der Gruppengröße resultieren und könnte somit viele Lerner dazu bringen, neue Gruppen zu bilden. Zusätzlich zur Gruppenzusammenstellung muss daher die Gruppenneuzusammenstellung als neues Thema in aktuellen Kontexten großer Lerner-Populationen ebenfalls erforscht werden. Die Untersuchungen der vorliegenden Arbeit gliedern sich in zwei Teile. Der erste Teil beschäftigt sich mit Gruppenzusammenstellung. In diesem Teil stelle ich einen diskreten-PSO Algorithmus zur Zusammenstellung kleiner Lerngruppen vor und vergleiche bislang bestehende Gruppenzusammenstellungs-Algorithmen unter den Gesichtspunkten Zeitaufwand und Gruppierungsqualität. Um Gruppenzusammenstellung in MOOCs anzuwenden wurde ein Gruppenzusammenstellungsexperiment in einem MOOC durchgeführt. Die Hauptergebnisse deuten darauf hin, dass die Gruppenzusammenstellung die Abbruchsquote reduzieren kann, jedoch lediglich einen sehr schwachen Bezug zur Lernperformanz der Lerner aufweist. Der zweite Teil beschäftigt sich mit Gruppenneuzusammenstellung. Die vorliegende Arbeit stellt eine datengesteuerte Herangehensweise vor, die umfassenden Gebrauch von Gruppeninteraktionsdaten macht sowie Gruppendynamik mit einbezieht. Mittels einer in einem Simulationsexperiment durchgeführten Evaluation zeigen sich die Vorteile dieses Verfahrens: Der Lerngruppenzusammenhalt wird verbessert und die Abbruchsquote im Vergleich zu einer Zufallsverteilung reduziert. Darüberhinaus wurde hier ein Gruppen-Lern-Werkzeug entwickelt und für die Praxis vorbereitet, das die Anforderungen des geforderten Ansatzes der Gruppenneuzusammenstellung erfüllt. / Small learning group composition addresses the problem of seeking such matching among a population of students that it could bring each group optimal benefits. Recently, many studies have been conducted to address this small group composition problem. Nevertheless, the focus of such a body of research has rarely been cast to large-scale contexts. Due to the recent come of MOOCs, the topic of group composition needs to be accordingly extended with new investigations in such large learning contexts. Different from classroom settings, the reported high drop-out rate of MOOCs could result in group’s incompletion in size and thus might compel many students to compose new groups. Thus, in addition to group composition, group re-composition as a new topic needs to be studied in current large-scale learning contexts as well. In this thesis, the research is structured in two stages. The first stage is group composition. In this part, I proposed a discrete-PSO algorithm to compose small learning groups and compared the existing group composition algorithms from the perspectives of time cost and grouping quality. To implement group composition in MOOCs, a group composition experiment was conducted in a MOOC. The main results indicate that group composition can reduce drop-out rate, yet has a very weak association with students’ learning performance. The second stage is to cope with group re-composition. This thesis suggests a data-driven approach that makes full use of group interaction data and accounts for group dynamics. Through evaluation in a simulation experiment, it shows its advantages of bringing us more cohesive learning groups and reducing the drop-out rate compared to a random condition. Apart from these, a group learning tool that fulfills the goals of the proposed group re-composition approach has been developed and is made ready for practice.