MOOCs: a systematic study of the published literature 2008-2012

Massive open online courses (MOOCs) are a recent addition to the range of online learning options. Since 2008, MOOCs have been run by a variety of public and elite universities, especially in North America. Many academics have taken interest in MOOCs recognising the potential to deliver education around the globe on an unprecedented scale; some of these academics are taking a research-oriented perspective and academic papers describing their research are starting to appear in the traditional media of peer reviewed publications. This paper presents a systematic review of the published MOOC literature (2008-2012): Forty-five peer reviewed papers are identified through journals, database searches, searching the Web, and chaining from known sources to form the base for this review. We believe this is the first effort to systematically review literature relating to MOOCs, a fairly recent but massively popular phenomenon with a global reach. The review categorises the literature into eight different areas of interest, introductory, concept, case studies, educational theory, technology, participant focussed, provider focussed, and other, while also providing quantitative analysis of publications according to publication type, year of publication, and contributors. Future research directions guided by gaps in the literature are explored.

Design patterns for promoting peer interaction in discussion forums in MOOCs

Design patterns are a way of sharing evidence-based solutions to educational design problems. The design patterns presented in this paper were produced through a series of workshops, which aimed to identify Massive Open Online Course (MOOC) design principles from workshop participants’ experiences of designing, teaching and learning on these courses. MOOCs present a challenge for the existing pedagogy of online learning, particularly as it relates to promoting peer interaction and discussion. MOOC cohort sizes, participation patterns and diversity of learners mean that discussions can remain superficial, become difficult to navigate, or never develop beyond isolated posts. In addition, MOOC platforms may not provide sufficient tools to support moderation. This paper draws on four case studies of designing and teaching on a range of MOOCs presenting seven design narratives relating to the experience in these MOOCs. Evidence presented in the narratives is abstracted in the form of three design patterns created through a collaborative process using techniques similar to those used in collective autoethnography. The patterns: “Special Interest Discussions”, “Celebrity Touch” and “Look and Engage”, draw together shared lessons and present possible solutions to the problem of creating, managing and facilitating meaningful discussion in MOOCs through the careful use of staged learning activities and facilitation strategies.

Typo-resource: developing T&L support materials through collaboration

This paper reports on a collaborative project between staff and students in the Department of Typography & Graphic Communication at the University of Reading The Partnerships in Learning and Teaching (PLanT) project here described is a direct response to student needs for better online support materials. Methodologically, the project embeds user-centred design principles within an iterative process of design development and participant research. This process has underpinned the development of a prototype for an online interface called Typo-Resource. The resulting initial prototype addresses the usability and user experience dimensions of an online learning resource, moving beyond providing tutor-identified sets of resources to a multifaceted, collaborative, and visual platform for peer learning.

Collaborating Blackboard into Teaching – Case Study

In this presentation, a business instructor will discuss a variety of Blackboard functions and describe how technology enhances teaching and learning. It will also address the challenges and issues facing both instructors and students in an online learning environment.

The Use of On-Line Computer adaptive Testing to raise Standardized Test Scores

Nursing school graduates are under pressure to pass the RN-NCLEX Exam on the first attempt since New York State monitors the results and uses them to evaluate the school’s nursing programs. Since the RN-NCLEX Exam is a standardized test, we sought a method to make our students better test takers. The use of on-line computer adaptive testing has raised our student’s standardized test scores at the end of the nursing course.

Distanslärares subjektiva teorier

I Sverige idag är det många som kompletterar sin gymnasieutbildning via kurser inom denkommunala vuxenutbildningen (komvux); och många gör det också på distans. För att synliggöradetta växande utbildningsområde som distansundervisningen utgör, fokuserar denna undersökning påde undervisande lärarnas tankar kring denna form av undervisning vid den kommunalavuxenutbildningen.Frågeställningen tar alltså upp vilka subjektiva teorier lärare inom distansundervisning (vid denkommunala vuxenutbildningen) har om sin distansundervisning; samt hur dessa subjektiva teorierförhåller sig till andra lärteorier. Som teori handlar Forskningsprogrammet ”Subjektive Theorien”om hur man vetenskapligt kan undersöka de teorier som människor har och uttrycker i vardagen.Teorins forskningsansats är inte att undersöka hur människor gör (handlingar), utan hur människortänker om sina handlingar, dvs. om deras kognitiva strukturer.För att undersöka detta valdes sex lärare ut vid en distansskola inom den kommunalavuxenutbildningen. Med dessa sex lärare genomfördes sedan semi-strukturerade narrativa intervjuer.Områden som behandlades var bland annat betygens reliabilitet – plagiat och fusk, elever i klassrumkontra på distans samt mer specifikt om hur lärarna såg på de elever som läser på distans. Ävenlärarnas syn på diskussion/grupparbete togs upp.Det som framkom var subjektiva teorier där lärarna var mycket utförliga, detaljerade ochnyancerade, samtidigt som det också framgick att lärarnas teoretiska kännedom om de olikaformerna av distansundervisning och om kopplingar till lärteorier var svagt utpräglad.

Uma contribuição ao estudo das categorias internas e de sua proliferação em redes ARTMAP

ART networks present some advantages: online learning; convergence in a few epochs of training; incremental learning, etc. Even though, some problems exist, such as: categories proliferation, sensitivity to the presentation order of training patterns, the choice of a good vigilance parameter, etc. Among the problems, the most important is the category proliferation that is probably the most critical. This problem makes the network create too many categories, consuming resources to store unnecessarily a large number of categories, impacting negatively or even making the processing time unfeasible, without contributing to the quality of the representation problem, i. e., in many cases, the excessive amount of categories generated by ART networks makes the quality of generation inferior to the one it could reach. Another factor that leads to the category proliferation of ART networks is the difficulty of approximating regions that have non-rectangular geometry, causing a generalization inferior to the one obtained by other methods of classification. From the observation of these problems, three methodologies were proposed, being two of them focused on using a most flexible geometry than the one used by traditional ART networks, which minimize the problem of categories proliferation. The third methodology minimizes the problem of the presentation order of training patterns. To validate these new approaches, many tests were performed, where these results demonstrate that these new methodologies can improve the quality of generalization for ART networks

Aspectos conceituais e instrumentais do conhecimento da prática do professor de cálculo diferencial e integral no contexto das tecnologias digitais

Pós-graduação em Educação Matemática - IGCE

Elaboração e avaliação de um ambiente virtual para o ensino/aprendizagem de embriologia

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

LABEXP - Laboratório de experimentação remota em tempo real

Este trabalho apresenta o processo de desenvolvimento e implementação do Laboratório de Experimentação Remota em Tempo Real (LabExp), atualmente em funcionamento na Universidade Federal do Pará, com o objetivo de funcionar como uma plataforma auxiliar para ensino e aprendizagem das disciplinas de sistemas de controle. O ensino e aprendizagem foram contemplados através da disponibilização de experimentos, onde os usuários poderão interagir com os mesmos, alterando parâmetros e observando o resultado desta interação. Além dos experimentos disponíveis, acredita-se que em ambientes de educação online é interessante disponibilizar aos alunos ferramentas que proporcionem maior interação entre alunos e professores e com o próprio laboratório remoto, proporcionando uma metodologia de aprendizado mais colaborativo, estimulando o aluno. Desta forma, são disponibilizadas aos alunos três aplicações: uma para envio de seus próprios experimentos; outra para interação com outros alunos, através de um fórum; e outra para o envio de suas opiniões/críticas. Antes do processo de desenvolvimento e implementação do LabExp, foi realizada uma análise sucinta sobre educação online, tendo em vista ser esta a finalidade do laboratório. Esta análise proporcionou maior conhecimento sobre esta metodologia de educação, orientando no restante do desenvolvimento do LabExp. Compreende-se que as tecnologias utilizadas não são determinantes para o desenvolvimento de um laboratório remoto, voltado para a educação online, entretanto experimentos remotos de sistemas de controle possuem uma restrição temporal, ou seja, necessitam obedecer a limites de tempo restritos, funcionando em tempo real. Para conseguir este comportamento foi utilizada a Real-Time Application Interface (RTAI), com o componente RTAI-XML. Além das tecnologias utilizadas, neste trabalho também é apresentado o processo de modelagem do LabExp, de acordo com padrões, princípios e recursos da Unified Modeling Language (UML) aplicada a aplicações web. Este processo de modelagem foi de fundamental importância, pois facilitou e orientou o desenvolvimento do laboratório.

Fóruns no ambiente Teleduc: reflexões sobre o papel dos mediadores e estratégias de gerenciamento de debates

Online discussion forums have been widely used in internet-mediated courses and blended courses. In these learning contexts, the mediator's (or tutor's) role in supporting successful learning is of considerable importance. Firstly, the present article discusses some studies in which the mediator's role in online learning environments is emphasized. Secondly, we use this discussion to support our qualitative case-study analysis, in which we investigated mediators' debate-management strategies in TelEduc virtual forums. Lastly, we propose a reflective framework about management strategies in forums in virtual learning platforms.

As contribuições do dialogismo de bakhtin e do signo em umberto eco para o ensino de língua estrangeira

This article discusses the dialogism in Mikhail Bakhtin and the grounds of the linguistic sign in Umberto Eco, with the intention to use the themes and authors, to support the teaching-learning methodologies of foreign language (English and Spanish) at the public school of São Paulo state. The conceptual approach of the two authors allows us to infer that learning a foreign language is effected by the appropriation of utterances and cultural knowledge, pedagogical concept that confronts the traditional method used in the São Paulo school, which is based mainly on grammar teaching and lexicons. The paper derives the theoretical research used to support a dissertation, posing and evaluates preliminary, the integration of traditional theaters in foreign language in public schools, with digital environments (in online courses), and also the educational effects -the use of audiovisual material at the classroom and online learning.

Reinforcement Lernen mit Regularisierungsnetzwerken

Die Arbeit behandelt das Problem der Skalierbarkeit von Reinforcement Lernen auf hochdimensionale und komplexe Aufgabenstellungen. Unter Reinforcement Lernen versteht man dabei eine auf approximativem Dynamischen Programmieren basierende Klasse von Lernverfahren, die speziell Anwendung in der Künstlichen Intelligenz findet und zur autonomen Steuerung simulierter Agenten oder realer Hardwareroboter in dynamischen und unwägbaren Umwelten genutzt werden kann. Dazu wird mittels Regression aus Stichproben eine Funktion bestimmt, die die Lösung einer "Optimalitätsgleichung" (Bellman) ist und aus der sich näherungsweise optimale Entscheidungen ableiten lassen. Eine große Hürde stellt dabei die Dimensionalität des Zustandsraums dar, die häufig hoch und daher traditionellen gitterbasierten Approximationsverfahren wenig zugänglich ist. Das Ziel dieser Arbeit ist es, Reinforcement Lernen durch nichtparametrisierte Funktionsapproximation (genauer, Regularisierungsnetze) auf -- im Prinzip beliebig -- hochdimensionale Probleme anwendbar zu machen. Regularisierungsnetze sind eine Verallgemeinerung von gewöhnlichen Basisfunktionsnetzen, die die gesuchte Lösung durch die Daten parametrisieren, wodurch die explizite Wahl von Knoten/Basisfunktionen entfällt und so bei hochdimensionalen Eingaben der "Fluch der Dimension" umgangen werden kann. Gleichzeitig sind Regularisierungsnetze aber auch lineare Approximatoren, die technisch einfach handhabbar sind und für die die bestehenden Konvergenzaussagen von Reinforcement Lernen Gültigkeit behalten (anders als etwa bei Feed-Forward Neuronalen Netzen). Allen diesen theoretischen Vorteilen gegenüber steht allerdings ein sehr praktisches Problem: der Rechenaufwand bei der Verwendung von Regularisierungsnetzen skaliert von Natur aus wie O(n**3), wobei n die Anzahl der Daten ist. Das ist besonders deswegen problematisch, weil bei Reinforcement Lernen der Lernprozeß online erfolgt -- die Stichproben werden von einem Agenten/Roboter erzeugt, während er mit der Umwelt interagiert. Anpassungen an der Lösung müssen daher sofort und mit wenig Rechenaufwand vorgenommen werden. Der Beitrag dieser Arbeit gliedert sich daher in zwei Teile: Im ersten Teil der Arbeit formulieren wir für Regularisierungsnetze einen effizienten Lernalgorithmus zum Lösen allgemeiner Regressionsaufgaben, der speziell auf die Anforderungen von Online-Lernen zugeschnitten ist. Unser Ansatz basiert auf der Vorgehensweise von Recursive Least-Squares, kann aber mit konstantem Zeitaufwand nicht nur neue Daten sondern auch neue Basisfunktionen in das bestehende Modell einfügen. Ermöglicht wird das durch die "Subset of Regressors" Approximation, wodurch der Kern durch eine stark reduzierte Auswahl von Trainingsdaten approximiert wird, und einer gierigen Auswahlwahlprozedur, die diese Basiselemente direkt aus dem Datenstrom zur Laufzeit selektiert. Im zweiten Teil übertragen wir diesen Algorithmus auf approximative Politik-Evaluation mittels Least-Squares basiertem Temporal-Difference Lernen, und integrieren diesen Baustein in ein Gesamtsystem zum autonomen Lernen von optimalem Verhalten. Insgesamt entwickeln wir ein in hohem Maße dateneffizientes Verfahren, das insbesondere für Lernprobleme aus der Robotik mit kontinuierlichen und hochdimensionalen Zustandsräumen sowie stochastischen Zustandsübergängen geeignet ist. Dabei sind wir nicht auf ein Modell der Umwelt angewiesen, arbeiten weitestgehend unabhängig von der Dimension des Zustandsraums, erzielen Konvergenz bereits mit relativ wenigen Agent-Umwelt Interaktionen, und können dank des effizienten Online-Algorithmus auch im Kontext zeitkritischer Echtzeitanwendungen operieren. Wir demonstrieren die Leistungsfähigkeit unseres Ansatzes anhand von zwei realistischen und komplexen Anwendungsbeispielen: dem Problem RoboCup-Keepaway, sowie der Steuerung eines (simulierten) Oktopus-Tentakels.

Towards a more effective model for distance education

What is the most effective model for academic distance education, given that drop-out numbers in traditional distance education institutions are too high and the demands from the various stakeholders are changing? In this paper this question is answered from the perspective of the Open University of the Netherlands (OUNL). The OUNL has planned to redesign its educational model from the traditional guided self-study model towards a model of active online learning. In essence this means that education will be less content driven; more focus is put on activating students to engage with real world problems supported by tutors and peers using distance media. The drivers for change, the change process and the resulting redesign of the educational model are presented in this paper.

Simple training tool is insufficient for appropriate diagnosis and treatment of malnutrition: A pre-post intervention study in a tertiary center.

OBJECTIVES To improve malnutrition awareness and management in our department of general internal medicine; to assess patients' nutritional risk; and to evaluate whether an online educational program leads to an increase in basic knowledge and more frequent nutritional therapies. METHODS A prospective pre-post intervention study at a university department of general internal medicine was conducted. Nutritional screening using Nutritional Risk Score 2002 (NRS 2002) was performed, and prescriptions of nutritional therapies were assessed. The intervention included an online learning program and a pocket card for all residents, who had to fill in a multiple-choice questions (MCQ) test about basic nutritional knowledge before and after the intervention. RESULTS A total of 342 patients were included in the preintervention phase, and 300 were in the postintervention phase. In the preintervention phase, 54.1% were at nutritional risk (NRS 2002 ≥3) compared with 61.7% in the postintervention phase. There was no increase in the prescription of nutritional therapies (18.7% versus 17.0%). Forty-nine and 41 residents (response rate 58% and 48%) filled in the MCQ test before and after the intervention, respectively. The mean percentage of correct answers was 55.6% and 59.43%, respectively (which was not significant). Fifty of 84 residents completed the online program. The residents who participated in the whole program scored higher on the second MCQ test (63% versus 55% correct answers, P = 0.031). CONCLUSIONS Despite a high ratio of malnourished patients, the nutritional intervention, as assessed by nutritional prescriptions, is insufficient. However, the simple educational program via Internet and usage of NRS 2002 pocket cards did not improve either malnutrition awareness or nutritional treatment. More sophisticated educational systems to fight malnutrition are necessary.