Change search
Refine search result
1 - 2 of 2
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    Nouri, Jalal
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    A socio-cultural model for orchestrating mobile learning activities2019In: International Journal of Technology Enhanced Learning, ISSN 1753-5255, E-ISSN 1753-5263, Vol. 11, no 2, p. 172-186Article in journal (Refereed)
    Abstract [en]

    Learning outdoors with mobile devices is associated with distinct challenges and constraints that needs to be taken into account when orchestrating formal mobile learning activities. In order to design pedagogically meaningful activities, we need to consider students scaffolding needs and have an understanding of the aspects that should be orchestrated for meeting those needs. This paper proposes an orchestration model for formal mobile learning activities across contexts that take such scaffolding needs into account. The model has been interactively developed based on empirical research conducted in three case-studies and have theoretical basis in sociocultural perspectives on learning, particularly resting on the concept of scaffolding and on the learning design sequence model of Selander. The model takes the orchestration of six scaffolding aspects into account, namely: the social (collaborative) aspects, the teachers, the technology, the physical context, the learning processes and tasks, and the modes and representations.

  • 2.
    Saqr, Mohammed
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Nouri, Jalal
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Fors, Uno
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Time to focus on the temporal dimension of learning: A learning analytics study of the temporal patterns of students’ interactions and self-regulationIn: International Journal of Technology Enhanced Learning, ISSN 1753-5255, E-ISSN 1753-5263Article in journal (Refereed)
    Abstract [en]

    Time dynamics is an important element of the self-regulated learning theory. Researchers have consistently reported that students who use time and learning strategies efficiently perform better than their counterparts who don’t. Likewise, there is a sufficient volume of evidence that supports the claim that delay in performing the learning tasks (procrastination) is a consistent negative predictor of academic achievement. Although temporality is an interesting aspect of learning processes, it is yet poorly studied. Therefore, in this learning analytics study, we attempt to better understand the role of temporality measures for the prediction of academic performance by using statistical modelling and applying machine learning methods.  

    The study included four online courses over a full year duration. Students were classified as low- and high achievers. Temporality was studied on daily, weekly, course-wise and year wise. The patterns of each performance group in each period were visually plotted and compared. Correlation with the performance was done. Visualizing the activities have highlighted a certain pattern. On the week level, early participation was a consistent predictor of high achievement. This finding was consistent from course to course and during most periods of the year. On an individual course level, high achievers were also likely to participate early and consistently. With a focus on temporal measures, we were able to predict high achievers with reasonable accuracy in each course.

    The study of temporality and how certain temporal patterns are more consistent have contributed to the production of a reasonably accurate and reproducible predictive models. These findings highlight the idea that temporality dimension is a significant source of information about learning patterns and has the potential to inform educators about students’ activities and to improve the accuracy and reproducibility of predicting students’ performance.

1 - 2 of 2
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf