Massive open online courses: a review of usage and evaluation

Sinclair, Jane; Boyatt, Russell; Rocks, Claire; Joy, Mike

doi:10.1504/ijlt.2015.069450

Cited by 38 publications

(26 citation statements)

References 37 publications

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“…Los artículos que lo mencionan indican que es uno de los elementos más complejos de desarrollar, debido a lo que implica el carácter masivo de los cursos (Robinson y Nelson 2015) y que los sistemas de feedback actual no responden a las necesidades de los usuarios (Sinclair et al 2015). El reto está en cómo incluir un mecanismo eficaz de evaluación que proporcione feedback a cientos o miles de estudiantes (Corke et al 2016;Comer y White 2016).…”

Section: Feedbackunclassified

“…Es lo que hemos denominado Learning Analytics. De hecho, los MOOC suponen para los investigadores en este ámbito (Sinclair et al 2015) una oportunidad única de poder usar los datos para, por ejemplo, intentar evitar la alta tasa de abandono en los MOOC. Algunos investigadores, como Comer et al (2014), incluso se plantean si el estudio de las métricas y los datos de un tipo de evaluación en concreto podría servir para predecir el éxito de un estudiante en un MOOC.…”

Section: Learning Analyticsunclassified

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The MOOC and student assessment: systematic review (2012-2016)

Vera

Calatayud²,

Espinosa

2017

@tic

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ResumenEste artículo se centra en el análisis de la evaluación en los MOOC. En primer lugar, analiza el concepto de MOOC y sus principales características. A partir de ahí, se lleva a cabo una revisión sistemática de la literatura científica más relevante producida entre 2012 y 2016 que aborda de modo específico los modelos y propuestas de evaluación del conocimiento adquirido por los alumnos que cursan MOOC. La búsqueda se ha realizado en las siguientes bases de datos: Web of Science, Scopus y EBSCOhost. Se han utilizado descriptores tanto en inglés como en español y, tras eliminar las duplicidades, se han analizado 110 artículos. El resultado es que las propuestas de evaluación más frecuentes son las pruebas objetivas automatizadas y la evaluación por pares, encontrando además que la evaluación por pares se utiliza tanto en los cMOOC como en los xMOOC.Palabras clave: evaluación; MOOC; revisión sistemática. ResumAquest article se centra en l'anàlisi de l'avaluació en els MOOC. En primer lloc, analitza el concepte de MOOC i les seves principals característiques. A partir d'ací, es porta a terme una revisió sistemàtica de la literatura científica més rellevant produïda entre 2012 i 2016 que aborda de manera específica els models i propostes d'avaluació del coneixement adquirit pels alumnes que cursen MOOC. La cerca s'ha fet en les següents bases de dades: Web of Science, Scopus i EBSCOhost. S'han utilitzat descriptors tant en anglès com en espanyol i, després d'eliminar les duplicitats, s'han analitzat 110 articles. El resultat és que les propostes d'avaluació més freqüents són les proves objectives automatitzades i l'avaluació per parells, trobant a més que l'avaluació per parells s'utilitza tant en els cMOOC com en els xMOOC.Paraules clau: avaluació; MOOC; revisió sistemàtica. AbstractThis article is based on the analysis of assessment in MOOC. Firstly, we study the concept, the types of MOOC and the main characteristics. From this point, we deal with a systematic revision of scientific literature from 2012 to 2016 in relation to assessment of students who are following a MOOC. This research has been done in these data base: Web of Science, Scopus and EBSCOhost. We have used both English and Spanish key words and finally we have analysed 110 articles. Our results show us that assessment models are usually based on tests with automatic feed-back and peer evaluation. Moreover, we have found that peer evaluation is used in xMOOC and also in cMOOC.

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Section: Feedbackunclassified

Section: Learning Analyticsunclassified

The MOOC and student assessment: systematic review (2012-2016)

Vera

Calatayud²,

Espinosa

2017

@tic

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“…However, there is still a large gap in MOOC research (Saadatmand & Kumpulainen, 2014;Sinclair, Boyatt, Rocks & Joy, 2014;Loizzo, 2015). This has multiple reasons such as data protection concerns, a tendency to hoard data conspire to curtail data sharing, ethical hurdles for qualitative research (Esposito, 2012;Reich, 2015).…”

Section: State Of the Art Of Mooc Research Trendsmentioning

confidence: 99%

Research Trends in Massive Open Online Course (MOOC) Theses and Dissertations: Surfing the Tsunami Wave

2016

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Massive Open Online Courses (MOOCs) have attracted a great deal of attention by higher education and private enterprises. MOOCs have evolved considerably since their emergence in 2008, all the while given rise to academic discussions on MOOC impact, design and reach. In an effort to understand MOOCs more comprehensively, this study analyzes theses and dissertations (N = 51) related to MOOCs and published between 2008 and 2015, identifying research trends from these academic documents. Theses and dissertations within this research scope were gathered through a comprehensive search in multiple academic databases. For the purposes of the study, the research employed a systematic review approach. In order to reveal trends in research themes, emphasize theoretical/conceptual backgrounds, research designs and models, first a document analysis was used to collect data and this was followed by a content analysis. Our research findings indicate that MOOC research is generally derived from education, engineering and computer science, as well as information and communication technology related disciplines. Qualitative methodology linked to a case study research model is most common, and the theoretical/conceptual backgrounds are usually distance education related. Remarkably, nearly half of the studies didn't benefit from any theoretical or conceptual perspectives. In sum, this study presents an evaluation regarding research trends derived from MOOC theses and dissertations, and provides directions for future MOOC research.

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“…This has continued as a constant theme in MOOC literature [33,37,20]. A meta-analysis of published data conducted by Jordan [21] indicates completion rates ranging from 0.9% to 36.1% with an average of 6.5%.…”

Section: Mooc Completionmentioning

confidence: 99%

Student engagement in massive open online courses

Sinclair

Kalvala

2016

IJLT

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Completion rates in Massive Open Online Courses (MOOCs) are disturbingly low. Existing analysis has focused on patterns of resource access and prediction of drop-out using learning analytics. In contrast, the effectiveness of teaching programs in traditional Higher Education (HE) settings internationally is increasingly assessed by surveys measuring student engagement. The conceptualisation of engagement used is much richer and more informative than the way the term is currently interpreted in the context of MOOCs. This paper considers MOOC participation, learning and drop-out in the context of this richer conceptualisation of student engagement. MOOC pedagogy and practice are examined and we evaluate how far HE engagement measures can be successfully used in the MOOC context. We identify the need for a MOOC engagement model and suggest recommendations for basic, initial steps which MOOC developers can make towards improving engagement.

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Massive open online courses: a review of usage and evaluation

Cited by 38 publications

References 37 publications

The MOOC and student assessment: systematic review (2012-2016)

The MOOC and student assessment: systematic review (2012-2016)

Research Trends in Massive Open Online Course (MOOC) Theses and Dissertations: Surfing the Tsunami Wave

Student engagement in massive open online courses

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