Change search
Refine search result
12 1 - 50 of 97
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.
    Aayesha, Aayesha
    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.
    Afzaal, Muhammad
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Wu, Yongchao
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Li, Xiu
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Weegar, Rebecka
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    An Ensemble Approach for Question-Level Knowledge Tracing2021In: Artificial Intelligence in Education: 22nd International Conference, AIED 2021, Utrecht, The Netherlands, June 14–18, 2021, Proceedings, Part II / [ed] Ido Roll; Danielle McNamara; Sergey Sosnovsky; Rose Luckin; Vania Dimitrova, Cham: Springer , 2021, p. 433-437Conference paper (Refereed)
    Abstract [en]

    Knowledge tracing—where a machine models the students’ knowledge as they interact with coursework—is a well-established area in the field of Artificial Intelligence in Education. In this paper, an ensemble approach is proposed that addresses existing limitations in question-centric knowledge tracing and achieves the goal of predicting future question correctness. The proposed approach consists of two models; one is Light Gradient Boosting Machine (LightGBM) built by incorporating all relevant key features engineered from the data. The second model is a Multiheaded-Self-Attention Knowledge Tracing model (MSAKT) that extracts historical student knowledge of future question by calculating their contextual similarity with previously attempted questions. The proposed model’s effectiveness is evaluated by conducting experiments on a big Kaggle dataset achieving an Area Under ROC Curve (AUC) score of 0.84 with 84% accuracy using 10fold cross-validation.

  • 2.
    Afzaal, Muhammad
    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.
    Aayesha, Aayesha
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Papapetrou, Panagiotis
    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.
    Wu, Yongchao
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Li, Xiu
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Weegar, Rebecka
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Automatic and Intelligent Recommendations to Support Students’ Self-Regulation2021In: International Conference on Advanced Learning Technologies (ICALT),, 2021, p. 336-338Conference paper (Refereed)
    Abstract [en]

    In this paper, we propose a counterfactual explanations-based approach to provide an automatic and intelligent recommendation that supports student's self-regulation of learning in a data-driven manner, aiming to improve their performance in courses. Existing work under the fields of learning analytics and AI in education predict students' performance and use the prediction outcome as feedback without explaining the reasons behind the prediction. Our proposed approach developed an algorithm that explains the root causes behind student's performance decline and generates data-driven recommendations for action. The effectiveness of the proposed predictive model that constitutes the intelligent recommendations is evaluated, with results demonstrating high accuracy.

  • 3.
    Afzaal, Muhammad
    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.
    Aayesha, Aayesha
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Papapetrou, Panagiotis
    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.
    Wu, Yongchao
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Li, Xiu
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Weegar, Rebecka
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Generation of Automatic Data-Driven Feedback to Students Using Explainable Machine Learning2021In: Artificial Intelligence in Education: 22nd International Conference, AIED 2021, Utrecht, The Netherlands, June 14–18, 2021, Proceedings, Part II / [ed] Ido Roll; Danielle McNamara; Sergey Sosnovsky; Rose Luckin; Vania Dimitrova, Springer , 2021, p. 37-42Conference paper (Refereed)
    Abstract [en]

    This paper proposes a novel approach that employs learning analytics techniques combined with explainable machine learning to provide automatic and intelligent actionable feedback that supports students self-regulation of learning in a data-driven manner. Prior studies within the field of learning analytics predict students’ performance and use the prediction status as feedback without explaining the reasons behind the prediction. Our proposed method, which has been developed based on LMS data from a university course, extends this approach by explaining the root causes of the predictions and automatically provides data-driven recommendations for action. The underlying predictive model effectiveness of the proposed approach is evaluated, with the results demonstrating 90 per cent accuracy.

  • 4.
    Afzaal, Muhammad
    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.
    Zia, Aayesha
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Papapetrou, Panagiotis
    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.
    Wu, Yongchao
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Li, Xiu
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Weegar, Rebecka
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Explainable AI for Data-Driven Feedback and Intelligent Action Recommendations to Support Students Self-Regulation2021In: Frontiers in Artificial Intelligence, E-ISSN 2624-8212, Vol. 4, article id 723447Article in journal (Refereed)
    Abstract [en]

    Formative feedback has long been recognised as an effective tool for student learning, and researchers have investigated the subject for decades. However, the actual implementation of formative feedback practices is associated with significant challenges because it is highly time-consuming for teachers to analyse students’ behaviours and to formulate and deliver effective feedback and action recommendations to support students’ regulation of learning. This paper proposes a novel approach that employs learning analytics techniques combined with explainable machine learning to provide automatic and intelligent feedback and action recommendations that support student’s self-regulation in a data-driven manner, aiming to improve their performance in courses. Prior studies within the field of learning analytics have predicted students’ performance and have used the prediction status as feedback without explaining the reasons behind the prediction. Our proposed method, which has been developed based on LMS data from a university course, extends this approach by explaining the root causes of the predictions and by automatically providing data-driven intelligent recommendations for action. Based on the proposed explainable machine learning-based approach, a dashboard that provides data-driven feedback and intelligent course action recommendations to students is developed, tested and evaluated. Based on such an evaluation, we identify and discuss the utility and limitations of the developed dashboard. According to the findings of the conducted evaluation, the dashboard improved students’ learning outcomes, assisted them in self-regulation and had a positive effect on their motivation.

    Download full text (pdf)
    fulltext
  • 5.
    Afzaal, Muhammad
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Zia, Aayesha
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences. Department of Informatics, Austria.
    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.
    Informative Feedback and Explainable AI-Based Recommendations to Support Students' Self-regulation2024In: Technology, Knowledge and Learning, ISSN 2211-1662, E-ISSN 2211-1670, Vol. 29, no 1, p. 331-354Article in journal (Refereed)
    Abstract [en]

    Self-regulated learning is an essential skill that can help students plan, monitor, and reflect on their learning in order to achieve their learning goals. However, in situations where there is a lack of effective feedback and recommendations, it becomes challenging for students to self-regulate their learning. In this paper, we propose an explainable AI-based approach to provide automatic and intelligent feedback and recommendations that can support the self-regulation of students' learning in a data-driven manner, with the aim of improving their performance on their courses. Prior studies have predicted students' performance and have used these predicted outcomes as feedback, without explaining the reasons behind the predictions. Our proposed approach is based on an algorithm that explains the root causes behind a decline in student performance, and generates data-driven recommendations for taking appropriate actions. The proposed approach was implemented in the form of a dashboard to support self-regulation by students on a university course, and was evaluated to determine its effects on the students' academic performance. The results revealed that the dashboard significantly enhanced students' learning achievements and improved their self-regulated learning skills. Furthermore, it was found that the recommendations generated by the proposed approach positively affected students' performance and assisted them in self-regulation

  • 6.
    Ahmed, Gashawa
    et al.
    Stockholm University, Faculty of Science, Department of Mathematics and Science Education.
    Nouri, Jalal
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Norén, Eva
    Stockholm University, Faculty of Science, Department of Mathematics and Science Education.
    Zhang, Lechen
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Students perceptions of programming in primary school2019In: WiPSCE'19: Proceedings of the 14th Workshop in Primary and Secondary Computing Education, Association for Computing Machinery (ACM), 2019, p. 1-5, article id 3Conference paper (Refereed)
    Abstract [en]

    Since autumn 2018, teachers throughout Sweden are obliged to relate to programming in one way or another in the teaching, especially in the subject of mathematics and technology education. Although teachers should formally work with programming teaching from the autumn of 2018, programming has been taught in primary school for several years. While there is some research on younger students, most of the research has almost exclusively focused on didactic approaches and strategies used by teachers, educational values and practices that accompany programming teaching, and views of teachers regarding programming teaching. What is still missing is research that highlights how younger students experience these new practices and how they primarily perceive programming in traditional school subjects, such as mathematics. Thus, this paper reports on a thematic analysis of younger students' (n=44) perceptions of programming; students who have been introduced to and been taught programming in mathematics in grade 5.

  • 7.
    Ahmed, Gashawa
    et al.
    Stockholm University, Faculty of Science, Department of Mathematics and Science Education.
    Nouri, Jalal
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Zhang, LeChen
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Norén, Eva
    Stockholm University, Faculty of Science, Department of Mathematics and Science Education.
    Didactic methods of integrating Programming in Mathematics in primary school: findings from a national project in Sweden2020In: SIGCSE '20: Proceedings of the 51st ACM Technical Symposium on Computer Science Education, Association for Computing Machinery (ACM), 2020, p. 261-267Conference paper (Refereed)
    Abstract [en]

    The association between mathematics and programming in an educational context is not new. Today, programming has been introduced into curricula worldwide for younger children. In the Swedish case, primary school teachers are expected to integrate programming in mathematics education from autumn 2018. However, Swedish teachers' knowledge of programming and programming didactics is limited. Meanwhile, there is little research on K-9 programming education. This has led to the dilemma that the mathematics teachers have limited support in didactic knowledge and good examples. This study reports on a teacher professional development project in programming. More specifically, teachers used Lesson Study to plan, execute, and evaluate lessons that integrated programming into various school subjects in elementary school. This study analyzed the didactic strategies developed in 10 lesson studies, as well as mapped the opportunities and challenges of pupils' learning in the mathematics subject. The result was the identification of three didactic strategies, which were analog programming, robot programming and block programming, as well as 11 didactic methods applied within these strategies. The paper contributes with examples of the didactic methods that teachers have developed and evaluated using lesson study. The paper further provides insights on how teachers can take progression into account by applying the three didactic strategies. At last but not least, the study shows a great need for teachers to develop computational thinking abilities.

  • 8.
    Bahati, Bernard
    et al.
    University of Rwanda, Rwanda.
    Fors, Uno
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Hansen, Preben
    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.
    Mukama, Evode
    University of Rwanda, Rwanda.
    Measuring Learner Satisfaction with Formative e-Assessment Strategies2019In: International Journal: Emerging Technologies in Learning, ISSN 1868-8799, E-ISSN 1863-0383, Vol. 14, no 7, p. 61-79Article in journal (Refereed)
    Abstract [en]

    The student experience with different aspects of online instructional settings has been the focus of educational practitioners and researchers in many studies. However, concerning technology-enabled formative assessment, little is known about student satisfaction regarding different possible formative e-assessment strategies the students are involved in. Using a 5-point Likert scale questionnaire, a web-based survey was developed to examine students’ satisfaction with the formative e-assessment strategies within an enriched virtual blended course. The results show that, in general, the students were satisfied with the quality of their engagement and the quality of feedback across all the formative e-assessment activities offered. The results also show that the student satisfaction varied between and within the formative e-assessment strategies. However, the gap between the student satisfaction mean ratings across all formative e-assessment strategies was marginal and could not help researchers decide upon which formative e-assessment strategy that stood out as the most preferred one. Learner satisfaction with different formative e-assessment strategies was positively correlated to each other at various levels but no relationship was found between students’ scores on the final course exam and learner satisfaction with formative e-assessment strategies. In the end, the study recommends a sustained and integrated use of the all three formative e-assessment strategies (online knowledge survey, online student-generated questions and peer-responses, and electronic reflective journals) in the context of hybrid courses. Further studies that would widen, diversify both the scope and the research instruments to investigate learner satisfaction with formative e-assessment strategies were also suggested.

  • 9.
    Bergdahl, Nina
    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.
    Covid-19 and Crisis-Promted Distance Education in Sweden2021In: Technology, Knowledge and Learning, ISSN 2211-1662, E-ISSN 2211-1670, Vol. 26, p. 443-459Article in journal (Refereed)
    Abstract [en]

    This study represents the first research effort to explore the transition from traditional teaching into distance teaching in Swedish schools enforced by covid-19. Governments made gradual and injudicious decisions to impede the spread of the pandemic (covid-19) in 2020. The enactment of new measures affected critical societal functions and included travel restrictions, closing of borders, school closures and lockdowns of entire countries worldwide. Social distancing became the new reality for many, and for many teachers and students, the school closure prompted a rapid transition from traditional to distance education. This study aims to capture the early stages of that transition. We distributed a questionnaire to teachers' (n = 153) to gain insights into teacher and school preparedness, plans to deliver distance education, and teachers' experience when making this transition. Results show that the school preparedness was mainly related to technical aspects, and that teachers lack pedagogical strategies needed in the emerging learning landscape of distance education. Findings reveal four distinct pedagogical activities central for distance education in a crisis, and many challenges faced during the transition. While preparedness to ensure continuity of education was halting, schools and teachers worked with tremendous effort to overcome the challenges. Results expand on previous findings on school closure during virus outbreaks and may in the short-term support teachers and school leaders in making informed decisions during the shift into distance education. The study may also inform the development of preparedness plans for schools, and offers a historical documentation.

  • 10.
    Bergdahl, Nina
    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.
    Student engagement and disengagement in TEL - The role of gaming, gender and non-native students2020In: Research in Learning Technology, ISSN 2156-7069, E-ISSN 2156-7077, Vol. 28, article id 2293Article in journal (Refereed)
    Abstract [en]

    Student engagement is critical for learning. However, little is known about engagement and disengagement and particular social groups. Recent research has alerted that engagement in technology-enhanced learning (TEL) settings may manifest differently than engagement in analogue learning settings. This study explores how different social groups of upper secondary school students (n= 410) engage and disengage when learning with digital technologies. We used an instrument to approach dimensions of engagement and disengagement in TEL. Using thematic analysis, we identified cognitive, emotional, behavioural and social aspects of engagement and disengagement in eight-student interviews which together with theory, informed a questionnaire. Using statistical methods, we explored the relationship between engagement, disengagement and the social categories: gamers, gender and non-native speakers. We found significant differences between the groups. For example: that high-frequency gaming students were not as easily distracted as students reporting low-frequency gaming, that female students engaged in TEL in different ways than male students, and that non-native speakers displayed significantly fewer tendencies to engage in unauthorised uses of digital technologies than native speakers. Identifying indicators reflecting engagement and disengagement in TEL in social groups can inform successful practices that stimulate student engagement and can be used to avoid, or redeem, group-specific challenges that trigger disengagement.

    Download full text (pdf)
    fulltext
  • 11.
    Bergdahl, Nina
    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.
    Disengagement, engagement and digital skills in technology-enhanced learning2020In: Education and Information Technologies: Official Journal of the IFIP technical committee on Education, ISSN 1360-2357, E-ISSN 1573-7608, Vol. 25, no 2, p. 957-983Article in journal (Refereed)
    Abstract [en]

    With the digitalisation of education increasing, the relationship between student engagement in Technology-enhanced Learning (TEL) and digital skills has remained largely unexplored. There is a strong consensus that engagement is necessary for students to succeed in school. We hypothesised that students reporting high and low levels of general engagement display differences in terms of their engagement in TEL, and that students’ digital skills correlate with their engagement in and disengagement in TEL, which in turn is related to their learning outcomes. We used statistical tests to explore the relationship between the students’ (N = 410) general engagement and engagement in TEL, and investigated how digital skills were related to engagement and disengagement in TEL. We found significant correlations between students’ digital skills and engagement in TEL, showing that the possession of high levels of digital skill is related to engagement in TEL. Interestingly, digital skills were not related to disengagement. This suggests that students reporting both high and low levels of digital skills disengage to some extent when learning with technologies. We also identified variables reflecting both engagement and disengagement in TEL that predict student performance as measured via final grades, implying that in order to understand and support students who learn with technologies, a broader understanding of the factors influencing engagement and disengagement is key.

  • 12.
    Bergdahl, Nina
    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.
    Knutsson, Ola
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Engagement, disengagement and performance when learning with technologies in upper secondary school2020In: Computers and education, ISSN 0360-1315, E-ISSN 1873-782X, Vol. 149, article id 103783Article in journal (Refereed)
    Abstract [en]

    Students need to engage in order to learn. As digitalisation changes the conditions for learning, it is essential to consider how student engagement might be affected. This study explores the relationship between students' level of engagement in technology-enhanced learning (TEL) and academic outcomes. More specifically, we developed and validated an instrument LET (Learner–Technology–Engagement) using principal component analysis and confirmatory factor analysis, and distributed this to second and third year upper secondary school students. We then matched student responses (n = 410) with their school grades. Using a bivariate correlation test, a one-way ANOVA test, and a post hoc test, we analysed the associations between low-, average-, and high-performance students and their reported engagement and disengagement when learning with technologies. The analysis reveals that high-performance students find it easier to concentrate when working with learning technologies than do average and low performers. We also found significant correlations between low grades and reported time spent on social media and streaming media for other purposes than learning (e.g., YouTube). There were also significant correlations between a decrease in students’ performance and the occurrence of unauthorised multi-tasking via learning technologies while in class: the lower the grades, the more frequently students reported using digital technologies to escape when lessons were boring. Conclusively: high-performance students seem to develop strategies to use digital technologies in supportive and productive ways. Thus, in order for schools to use digital technologies to ensure that disadvantaged students do not remain disadvantaged when learning with technologies and to not replicate problems in analogue classroom interactions, insights how different performance groups engage and disengage in TEL is critical for learning.

  • 13.
    Bergdahl, Nina
    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.
    Karunaratne, Thashmee
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Afzaal, Muhammad
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Saqr, Mohammad
    KTH Royal Institute of Technology, Sweden.
    Learning Analytics for Blended Learning: A Systematic Review of Theory, Methodology, and Ethical Considerations2020In: International journal of learning analytics and artificial intelligence for education, E-ISSN 2706-7564, Vol. 2, no 2, p. 46-79Article in journal (Refereed)
    Abstract [en]

    Learning Analytics (LA) approaches in Blended Learning (BL) research is becoming an established field. In the light of previous critiqued toward LA for not being grounded in theory, the General Data Protection and a renewed focus on individuals’ integrity, this review aims to explore the use of theories, the methodological and analytic approaches in educational settings, along with surveying ethical and legal considerations. The review also maps and explores the outcomes and discusses the pitfalls and potentials currently seen in the field. Journal articles and conference papers were identified through systematic search across relevant databases. 70 papers met the inclusion criteria: they applied LA within a BL setting, were peer-reviewed, full-papers, and if they were in English. The results reveal that the use of theoretical and methodological approaches was disperse, we identified approaches of BL not included in categories of BL in existing BL literature and suggest these may be referred to as hybrid blended learning, that ethical considerations and legal requirements have often been overlooked. We highlight critical issues that contribute to raise awareness and inform alignment for future research to ameliorate diffuse applications within the field of LA.

  • 14.
    Cerratto Pargman, Teresa
    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.
    Milrad, Marcelo
    Taking an instrumental genesis lens: New insights into collaborative mobile learning2018In: British Journal of Educational Technology, ISSN 0007-1013, E-ISSN 1467-8535, Vol. 49, no 2, p. 219-234Article in journal (Refereed)
    Abstract [en]

    In this paper, we argue that in order to gain a deeper understanding of collaborative mobile learning in schools, it is important to know not only how mobile devices affect collaborative learning but also how collaborative learning emerges and is mediated by these devices. We develop our argument by applying the instrumental genesis theory and the collective instrumented activities and situations model for the analysis of learners' collaborative learning in the tablet-mediated classroom. This analysis is grounded in data collected in four elementary Swedish schools (ie, from fourth to eighth grade). From the data, we considered the learners' conversation in English as a foreign language, inquiry-based learning in the natural sciences classroom and game-based learning in the arithmetic classroom. On the one hand, the scrutiny of these specific activities led us to distinguish the pragmatic, epistemic, and reflexive instrumental mediations that have already been theorized in the instrumental genesis theory. On the other hand, they helped us to identify two additional ones, which we call emotional and spatial. Based on these findings, we claim that collaboration in the tablet-mediated classroom is a complex activity that emerges from a variety of instrumental mediations that configure contemporary collaborative mobile learning.

  • 15.
    Cerratto-Pargman, Teresa
    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.
    One Tablet, Multiple Epistemic Instruments in the Everyday Classroom2017In: Data Driven Approaches in Digital Education: Proceedings / [ed] Élise Lavoué, Hendrik Drachsler, Katrien Verbert, Julien Broisin, Mar Pérez-Sanagustín, Springer, 2017, p. 379-384Conference paper (Refereed)
    Abstract [en]

    Grounded in the analyses of 23 semi-structured interviews and 31 field notes from classroom observations, this study scrutinizes the relationships that teachers and learners entertain with/through the tablet in their process of technology appropriation in the classroom. The results reveal that, on the one hand, the learners elaborate a variety of instruments from their interactions with the tablet and, on the other hand, that the teachers’ appropriation plays a central role in configuring a creative, critical and participatory pedagogy in the contemporary classroom.

  • 16.
    Cerratto-Pargman, Teresa
    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.
    Tablets in the CSCL Classroom: A Lens on Teachers’ Instrumental Geneses2017In: Making a Difference: Prioritizing Equity and Access in CSCL: 12th International Conference on Computer Supported Collaborative Learning (CSCL) 2017, Volume 2 / [ed] Brian K. Smith, Marcela Borge, Emma Mercier, Kyu Yon Lim, International Society of the Learning Sciences, 2017, p. 837-838Conference paper (Refereed)
    Abstract [en]

    Most educational research on tablets in schools seeks to find out whether children learn more efficiently with or without such devices. This study differs from such research as it instead investigates how tablets take part in the everyday CSCL classroom? Grounded in the instrumental genesis theory, this study focuses on the multifarious relationships between teacher-tablets-learner(s) to inform the processes of tablet appropriation in the classroom. Analysis of the instrumental processes observed reveals that learners on the one hand develop usage schemes that challenge those developed by the teachers. Teachers on the other hand are forced to review their competence, rethinking power-relationships vis-à-vis learners and have to reflect/design a creative, critical and participatory pedagogical practice that is aligned with learners’ utilization schemes and the instruments they bring to our contemporary classrooms.

  • 17. Chibas, Åsa
    et al.
    Nouri, Jalal
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Norén, Eva
    Stockholm University, Faculty of Science, Department of Mathematics and Science Education.
    Zhang, Lechen
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Sjöberg, Christer
    Didactical strategies and challenges when teaching programming in pre-school2018In: EDULEARN18: Proceedings, The International Academy of Technology, Education and Development, 2018, p. 3345-3350Conference paper (Refereed)
    Abstract [en]

    Many countries around the world have introduced programming curriculum at K-9 level. For a number of years, a lot of studies have surfaced demonstrating enactments of programming education, for instance through the use of visual programming languages as Scratch in different contexts. However, these studies have had a dominating focus on students of age 7 and older and there are few studies reporting on implementation of programming activities for younger children at preschool. This gap is addressed by this study that focus exclusively on learning of programming in a preschool class of six year olds. We have followed one teacher during six months conducting both classroom observations and interviews. In this paper we report on the didactical methods the teacher used when teaching programming through unplugged (analogue) means, with BlueBot robots, and through Scratch Jr. We end the paper by a discussion reflecting on challenges and lessons learned in relation to introducing programming for young children.

  • 18. Chibás, Åsa
    et al.
    Nouri, Jalal
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Norén, Eva
    Stockholm University, Faculty of Science, Department of Mathematics and Science Education.
    Zhang, Lechen
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Att främja datalogiskt tänkande i förskoleklassen2022In: Skolportens artikelserie Leda & Lära, Vol. 3, p. 3-29, article id 3Article in journal (Refereed)
    Abstract [sv]

    I MÅNGA LÄNDER världen runt har digitalisering och programmering införts i läroplaner för förskola och grundskola. Under senare tid har flera studier om undervisning i programmering i olika sammanhang genomförts. Dessa studier har oftast haft fokus på elever från 7 år och äldre och det finns få studier som rapporterar om införandet av programmering för barn i förskola och yngre elever i förskoleklass. Denna klyfta hanterar vi i denna studie som fokuserar på programmering och utveckling av elevers datalogiska tänkande i förskoleklass. Hösten 2017 startade Ifous (Innovation, forskning och utveckling i skola och förskola) ett forsknings- och utvecklingsprogram med fokus på utveckling av didaktiska modeller för programmering i utbildningen från förskola till och med grundskolan. Programmet avslutades våren 2020. I detta program deltog skolor från fem skolhuvudmän, Tyresö kommun, Åstorps kommun, Simrishamns kommun, Stockholms stad och Freinetskolan Hugin i Norrtälje. Programmet som sådant innebar viss kompetensutveckling och främjade forskning om programmeringsundervisning från förskoleklass till och med årskurs 9 i grundskolan. I denna artikel presenterar vi hur en lärare arbetade med programmering för att främja datalogiskt tänkande hos elever i förskoleklass under treårsperioden och den erfarenhet som hon förvärvat. I artikeln drar vi slutsatsen att förskoleklasselever med systematisk och tankeväckande didaktisk modellering fullt ut kan utveckla ett antal grundläggande datalogiska färdigheter.

    Download full text (pdf)
    Att främja datalogiskt tänkade i förskoleklassen
  • 19.
    Eliasson, Johan
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Cerratto-Pargman, Teresa
    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.
    Spikol, Daniel
    Linnaeus University.
    Ramberg, Robert
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Mobile Devices as Support Rather than Distraction for Mobile Learners: Evaluating Guidelines for Design2011In: International Journal of Mobile and Blended Learning, ISSN 1941-8647, E-ISSN 1941-8655, Vol. 3, no 2, p. 1-15Article in journal (Refereed)
    Abstract [en]

    This article questions the design of mobile learning activities that lead students to spend time focusing on the mobile devices at the expense of interacting with other students or exploring the environment. This problem is approached from an interaction design perspective, designing and analysing geometry-learning activities. The authors present six guidelines for designing mobile learning activities, where mobile devices support rather than distract students from contents and contexts relevant to the learning goals. The guidelines are developed through video analysis of groups of middle school students doing learning activities outdoors and evaluated using the task model. The guidelines suggest that students (1) assume roles based on a different functionality of each device, (2) use devices as contextual tools, that the activities, (3) include physical interaction with the environment, (4) let teachers assume roles, (5) encourage face-to-face communication, and (6) introduce students to the mobile devices.

  • 20.
    Eliasson, Johan
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Knutsson, Ola
    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.
    Karlsson, Olov
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Ramberg, Robert
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Cerratto-Pargman, Teresa
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Evaluating Interaction with Mobile Devices in Mobile Inquiry-Based Learning2012In: WMUTE '12 Proceedings of the 2012 IEEE Seventh International Conference on Wireless, Mobile and Ubiquitous Technology in Education, Washington, DC, USA: IEEE Computer Society, 2012, p. 92-96Conference paper (Refereed)
    Abstract [en]

    We evaluate to what extent students are interacting with mobile devices in one of four ways intended in the design of a mobile learning activity. Video data from one class of fifth grade students were analyzed using a model of four different types of interaction. The evaluation shows that the students interacted with the devices in the ways intended in design 64% of the time. The contribution is an approach for translating learning goals to interaction design goals in mobile learning research. We conclude that this approach can be of value in designing and evaluating interaction with mobile devices for an entire mobile learning activity.

  • 21.
    Eliasson, Johan
    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.
    Ramberg, Robert
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Cerratto-Pargman, Teresa
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Design Heuristics for Balancing Visual Focus on Devices in Formal Mobile Learning Activities2010In:  , 2010Conference paper (Other academic)
  • 22.
    Hansson, Karin
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Talantsev, Anton
    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.
    Ekenberg, Love
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Lindgren, Tony
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Open government ideologies in post-soviet countries2016In: International Journal of Electronic Governance, ISSN 1742-7509, E-ISSN 1742-7517, Vol. 8, no 3, p. 244-264Article in journal (Refereed)
    Abstract [en]

    Most research in research areas like e-government, e-participation and open government assumes a democratic norm. The open government (OG) concept is commonly based on a general liberal and deliberative ideology emphasising transparency, access, participation and collaboration, but were also innovation and accountability are promoted. In this paper, we outline a terminology and suggest a method for how to investigate the concept more systematically in different policy documents, with a special emphasis on post-soviet countries. The result shows that the main focus in this regions OG policy documents is on freedom of information and accountability, and to a lesser extent on collaboration, while other aspects, such as diversity and innovation, are more rarely mentioned, if at all.

  • 23.
    Hedberg, Hillevi
    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.
    Hansen, Preben
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Rahmani, Rahim
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    A Systematic Review of Learning Trough Mobile Augmented Reality2018In: International Journal of Interactive Mobile Technologies (iJIM), E-ISSN 1865-7923, Vol. 12, no 3, p. 75-85Article in journal (Refereed)
    Abstract [en]

    In the beginning of 2000, researchers started to see the potential of using Augmented Reality (AR) in educational and foresaw that further research within the field. Since then, AR research have taken many different approaches. This is also true for AR in relation to pedagogical purposes. This study is to investigate what has been studied within the AR field related to mobile augmented reality. It attempts to make systematic review of how learning and pedagogical aspects have been approached in the articles. In recent years, mobile augmented reality has become increasingly interesting due to the mobile devices small form factors and their ability to let the students move around freely while learning. The aim of this study is to make a systematic review of pedagogical uses of mobile augmented reality. Based on a review of previous literature of mobile AR systems for pedagogical purposes, published between 2000-2017, make it possible to see in which direction mobile AR systems for education are heading and how future mobile AR systems should be designed to best fit the needs of future students so they can more effectively improve their learning.

  • 24.
    Hegestedt, Robert
    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.
    Rundquist, Rebecka
    Linnaeus University, Växjö, Sweden.
    Fors, Uno
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Data-driven school improvement and data-literacy in K-12: Findings from a Swedish national program2023In: International Journal: Emerging Technologies in Learning, ISSN 1868-8799, E-ISSN 1863-0383, Vol. 18, no 15, p. 189-208Article in journal (Refereed)
    Abstract [en]

    Data-driven school improvement has been proposed to improve and support edu-cational practices and more studies are emerging describing data-driven practices in schools and the effects of data-driven interventions. This paper reports on a study that has taken place within a national program where 15 schools from six different municipalities and organizations are working at classroom, school and municipality levels to improve educational practices using data-driven methods. The study aimed at understanding what educational problems teachers, principals and administrative staff in the project aimed to address through the utilization of data-driven methods and the challenges they face in doing so. Using a mixed method design, we identified four thematic areas that reflect the focused problem areas of the participants in the project, namely didactics, democracy, assessment and planning, and mental health. All development groups identified problems that can be solved with data-driven methods. Along with this, we also identified five challenges faced by the participants: time and resources, competence, ethics, digi-tal systems and common language. We conclude that the main challenge faced by the participants is data literacy, and that professional development is needed to support effective and successful data-driven practices in schools.

  • 25.
    Li, Xiu
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Henriksson, Aron
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Duneld, Martin
    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.
    Wu, Yongchao
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Evaluating Embeddings from Pre-Trained Language Models and Knowledge Graphs for Educational Content Recommendation2024In: Future Internet, E-ISSN 1999-5903, Vol. 16, no 1, p. 1-21Article in journal (Refereed)
    Abstract [en]

    Educational content recommendation is a cornerstone of AI-enhanced learning. In particular, to facilitate navigating the diverse learning resources available on learning platforms, methods are needed for automatically linking learning materials, e.g. in order to recommend textbook content based on exercises. Such methods are typically based on semantic textual similarity (STS) and the use of embeddings for text representation. However, it remains unclear what types of embeddings should be used for this task. In this study, we carry out an extensive empirical evaluation of embeddings derived from three different types of models: (i) static embeddings trained using a concept-based knowledge graph, (ii) contextual embeddings from a pre-trained language model, and (iii) contextual embeddings from a large language model (LLM). In addition to evaluating the models individually, various ensembles are explored based on different strategies for combining two models in an early vs. late fusion fashion. The evaluation is carried out using digital textbooks in Swedish for three different subjects and two types of exercises. The results show that using contextual embeddings from an LLM leads to superior performance compared to the other models, and that there is no significant improvement when combining these with static embeddings trained using a knowledge graph. When using embeddings derived from a smaller language model, however, it helps to combine them with knowledge graph embeddings. The performance of the best-performing model is high for both types of exercises, resulting in a mean Recall@3 of 0.96 and 0.95 and a mean MRR of 0.87 and 0.86 for quizzes and study questions, respectively, demonstrating the feasibility of using STS based on text embeddings for educational content recommendation. The ability to link digital learning materials in an unsupervised manner -- relying only on readily available pre-trained models -- facilitates the development of AI-enhanced learning.

    Download full text (pdf)
    fulltext
  • 26.
    Li, Xiu
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Henriksson, Aron
    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.
    Duneld, Martin
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Wu, Yongchao
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Linking Swedish Learning Materials to Exercises through an AI-Enhanced Recommender System2023In: Methodologies and Intelligent Systems for Technology Enhanced Learning, 13th International Conference / [ed] Marcelo Milrad, Nuno Otero, María Cruz Sánchez‑Gómez, Juan José Mena, Dalila Durães, Filippo Sciarrone, Claudio Alvarez-Gómez, Manuel Rodrigues, Pierpaolo Vittorini, Rosella Gennari, Tania Di Mascio, Marco Temperini, Fernando De la Prieta, Cham: Springer, 2023, p. 96-107Conference paper (Refereed)
    Abstract [en]

    As an integral part of AI-enhanced learning, a content recommender automatically filters and recommends relevant learning materials to the learner or the instructor in a learning system. It can effectively help instructors in pedagogical practices and support students in self-regulated learning. Content recommendation technologies and applications have been studied extensively, however, the SOTA technologies have not adequately adapted to the education domain and there is very limited research on how different models and solutions can be applied in the Swedish context and for multiple subjects. In this paper, we develop a text similarity-based content recommender system. Specifically, given a quiz, we automatically recommend supportive learning resources as a reference to the answer and link back to the textbook sections where the examined knowledge points reside. We present a generic method for Swedish educational content recommendations using the most representative models, evaluate and analyze in multi-dimensions such as model types, pooling methods, subjects etc. The best results are obtained by Sentence-BERT (SBERT) with max paragraph-level pooling, outperforming traditional Natural Language Processing (NLP) models and knowledge graph-based models, obtaining on average 95% in Recall@3 and 82% in MRR, and outstanding in dealing with texts containing symbols, equations or calculations. This research provides empirical evidence and analysis, and can be used as a guidance when building a Swedish educational content recommender.

  • 27.
    Li, Xiu
    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.
    Henriksson, Aron
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Duneld, Martin
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Wu, Yongchao
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Automatic Educational Concept Extraction Using NLP2022In: Methodologies and Intelligent Systems for Technology Enhanced Learning, 12th International Conference / [ed] Marco Temperini; Vittorio Scarano; Ivana Marenzi; Milos Kravcik; Elvira Popescu; Rosa Lanzillotti; Rosella Gennari; Fernando De la Prieta; Tania Di Mascio; Pierpaolo Vittorini, Springer Nature , 2022, p. 133-138Conference paper (Refereed)
    Abstract [en]

    Educational concepts are the core of teaching and learning. From the perspective of educational technology, concepts are essential meta-data, represen- tative terms that can connect different learning materials, and are the foundation for many downstream tasks. Some studies on automatic concept extraction have been conducted, but there are no studies looking at the K-12 level and focused on the Swedish language. In this paper, we use a state-of-the-art Swedish BERT model to build an automatic concept extractor for the Biology subject using fine- annotated digital textbook data that cover all content for K-12. The model gives a recall measure of 72% and has the potential to be used in real-world settings for use cases that require high recall. Meanwhile, we investigate how input data fea- tures influence model performance and provide guidance on how to effectively use text data to achieve the optimal results when building a named entity recognition (NER) model.

  • 28.
    Lindgren, Tony
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Ekenberg, Love
    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.
    Hansson, Karin
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    An Open Government Index: from Democracy to Efficiency to Innovation2014In: DSV writers hut 2014: proceedings, Stockholm: Department of Computer and Systems Sciences, Stockholm University , 2014Conference paper (Other academic)
    Abstract [en]

    Most research in research areas like E-government, E-participation and Open government assume a democratic norm. The concept of Open government, recently promoted by, e.g., The Obama administration and the European Commission is to a large extent based on a general liberal and deliberative ideology emphasizing transparency, participation and collaboration. The concept has also become of interest for states like China and Singapore. In this position paper we outline how to study the concept under different political discourses and suggest an Open government index that can be used to analyze the concept of open government under various settings.

  • 29.
    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.

  • 30.
    Nouri, Jalal
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    A theoretical grounding of learning mathematics in authentic real-world contexts supported by mobile technology2012In: Proceedings of the IADIS International Conference Mobile Learning / [ed] Inmaculada Arnedillo Sánchez and Pedro Isaías, 2012Conference paper (Refereed)
    Abstract [en]

    The problems associated with de-contextualized learning are prominently accentuated in abstract and strongly formalized educational subjects such as mathematics. As means to overcome these problems, the research domain of mathematics education has repeatedly called for situated, embodied and multimodal ways of learning. Interestingly, with the emergence of mobile learning, and through the affordances of mobile technology, opportunities are offered to extend the education of mathematics to authentic contexts for these kinds of learning practices. In this paper we give an account of theories on situated learning/cognition, multimodality, and embodied learning, and present four empirical studies on mobile mathematical learning characterized according to these theories. The paper contributes with a theoretical grounding for mobile mathematical learning.

  • 31.
    Nouri, Jalal
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Digital kompetens i informationssamhället2018In: Att bli lärare / [ed] Eva Insulander, Staffan Selander, Liber, 2018, p. 254-259Chapter in book (Other academic)
  • 32.
    Nouri, Jalal
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Editorial of the First Issue of the International Journal of Learning Analytics and Artificial Intelligence for Education2019In: International journal of learning analytics and artificial intelligence for education, ISSN 2706-7564, Vol. 1, no 1, p. 4-7Article in journal (Other academic)
    Abstract [en]

    In this editorial, the first issue of the International Journal of Learning Analytics and Artificial Intelligence for Education is presented. The Journal of Learning Analytics and Artificial Intelligence for Education is a peerreviewed, open access journal that aim to disseminate highest quality research in the field. The journal aims to increase knowledge and understanding of ways in which learning analytics and artificial intelligence can support and enhance education. The editorial presents the scope and fields of interest for the journal, and an overview of the articles published in the first issue.

  • 33.
    Nouri, Jalal
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Eliciting the potentials of mathematical mobile learning trough scaffolding learning processes across contexts2012In: International Journal of Mobile Learning and Organisation, ISSN 1746-725X, E-ISSN 1746-7268, Vol. 6, no 3/4, p. 285-302Article in journal (Refereed)
    Abstract [en]

    Little is understood in terms of scaffolding learning processes in more dynamical contexts than the classroom environment. The scope of mobile learning research has so far been limited to the scaffolding functions of the mobile technology. Thus, in this paper, a larger grip was taken, focusing on all available means, such as teachers, mobile technology, pre- and post-activities as supportive structures. In doing that a sequence of learning activities were designed within the domain of mathematics education. We asked what scaffolding role the available resources can play in supporting the students learning processes, and further, how we are to orchestrate these resources across contexts in a pedagogical manner. The findings demonstrates how students' learning processes are to be scaffolded and how learning in an outdoor context can be meaningfully supported through the sequencing of activities and the utilisation of pre- and post-activities in indoor contexts.

  • 34.
    Nouri, Jalal
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Forskningsinsatsens genomförande och resultat2020In: Programmering i skolan: vad, hur, när och varför?: Slutrapport från FoU-programmet Programmering i ämnesundervisningen / [ed] Anette Jahnke, Stockholm: Ifous , 2020, p. 35-49Chapter in book (Other academic)
    Download full text (pdf)
    fulltext
  • 35.
    Nouri, Jalal
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Mobile Inquiry-based Learning – a hype?2014In: Conference proceedings: 4th international Designs for Learning conference 6-9th May 2014, Stockholm: Stockholm University, 2014Conference paper (Refereed)
  • 36.
    Nouri, Jalal
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Orchestrating scaffolded outdoor mobile learning activities2014Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Since the beginning of time, technological innovations have formed the basis for the development of society and supported the most fundamental societal features. The educational system is no exception. This we have witnessed on many occasions, as for example in form of the transformations of learning and teaching introduced by the printing press, the calculator and computers. With the advance of mobile technology, we have received another technology that inspires research fields to study the learning and teaching potentials that mobile technology may present. It is from here this thesis takes its general starting point, namely, in the determination to critically examine the role mobile technology can play in supporting outdoor learning activities. More specifically, the thesis attempts to, on the one hand, develop an understanding of the challenges and limitations associated with scaffolding students’ mobile learning in outdoor environments. On the other hand, based on such a developed understanding, the thesis investigates how mobile technology-supported outdoor activities should be orchestrated to scaffold students learning. Orchestration is, in this thesis, understood as the process of productively coordinating supportive interventions across multiple learning activities occurring at multiple social levels involving multiple contexts, and multiple tools and media.The framework of design-based research has guided the methodological approach. Three design studies formed the empirical basis of the study of the issues. The results of the thesis indicate the difficulties and challenges in supporting students in outdoor contexts and delineate an understanding of how mobile outdoor learning activities can be orchestrated with students scaffolding needs taken into account.The thesis contributes with a conceptualization of and a model for orchestration of mobile learning activities, a framework for design-based research in mobile learning, as well as a critical perspective on the introduction of mobile technology in education. 

    Download full text (pdf)
    Orchestrating scaffolded outdoor mobile learning activities
    Download (jpg)
    Omslagsframsida
  • 37.
    Nouri, Jalal
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Students Multimodal Literacy and Design of Learning During Self-Studies in Higher Education2019In: Technology, Knowledge and Learning, ISSN 2211-1662, E-ISSN 2211-1670, Vol. 24, no 4, p. 683-698Article in journal (Refereed)
    Abstract [en]

    Information and communication technologies have increasingly been integrated in our everyday lives, and as many would say changed how we acquire knowledge and how we learn. It is against such a background this paper will describe how higher education students engage with technology during self-studies and how they in particular utilize different semiotic affordances of information and communication technologies in order to learn course content. Consequently, focus is put on how university students design their learning during self-studies through exploiting multimodal literacy and by constructing knowledge through different modes and media. The paper reports on a mixed-method study and presents findings that points to that (1) students are becoming active designers of learning due to access to new modes and media that can be tailored to their needs, (2) that students have developed a multimodal digital literacy to various degrees, and (3) that students are provided opportunities for enhanced and more effective learning than before because of the availability of affordances of contemporary technology. Thus the paper calls for a pedagogical shift that take departure from a design-oriented, multimodal understanding of learning.

  • 38.
    Nouri, Jalal
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    The flipped classroom: for active, effective and increased learning - especially for low achievers2016In: International journal of educational technology in higher education, ISSN 2365-9440, Vol. 13, article id 33Article in journal (Refereed)
    Abstract [en]

    Higher education has been pressured to shift towards more flexible, effective, active, and student-centered teaching strategies that mitigate the limitations of traditional transmittal models of education. Lately, the flipped classroom model has been suggested to support this transition. However, research on the use of flipped classroom in higher education is in its infancy and little is known about student's perceptions of learning through flipped classroom. This study examined students' perceptions of flipped classroom education in a last year university course in research methods. A questionnaire was administered measuring students' (n = 240) perceptions of flipped classroom in general, video as a learning tool, and Moodle (Learning Management System) as a supporting tool within the frame of a flipped classroom model. The results revealed that a large majority of the students had a positive attitude towards flipped classroom, the use of video and Moodle, and that a positive attitude towards flipped classroom was strongly correlated to perceptions of increased motivation, engagement, increased learning, and effective learning. Low achievers significantly reported more positively as compared to high achievers with regards to attitudes towards the use of video as a learning tool, perceived increased learning, and perceived more effective learning.

  • 39.
    Nouri, Jalal
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Cerratto-Pargman, Teresa
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Characterizing Learning Mediated by Mobile Technologies: A Cultural-Historical Activity Theoretical Analysis2015In: IEEE Transactions on Learning Technologies, ISSN 1939-1382, E-ISSN 1939-1382, Vol. 8, no 4, p. 357-366Article in journal (Refereed)
    Abstract [en]

    Mobile technologies have not yet triggered the knowledge revolution in schools anticipated, in particular, by the telecommunications industry. On the contrary, mobile technologies remain extensively used outside the frontiers of formal education. The reasons for this are many and varied. In this paper, we concentrate on those associated with the prevalent methodological weakness in the study of innovative educational interventions with mobile technologies. In this context, the paper investigates the following question: what is the potential of second-generation cultural-historical activity theory (CHAT) for characterizing learning activities mediated by mobile technologies? To this end, an empirical study was designed with the goal of examining five small groups of students (fifth grade, age 12) who were using mobile devices in authentic educational settings, within a natural science inquiry-based learning activity outdoors. Second-generation CHAT was operationalized as an analytical and dialectic methodological framework for understanding learning activities mediated by mobile devices. The study contributes a characterization of mobile learning and identification of constraints and transformations introduced by mobile technology into students’ tasks.

  • 40.
    Nouri, Jalal
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Cerratto-Pargman, Teresa
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Pekplattor, undervisning och lärande2017In: Didaktik i omvandlingens tid: text, representation, design / [ed] Eva Insulander, Susanne Kjällander, Fredrik Lindstrand, Anna Åkerfeldt, Stockholm: Liber, 2017, p. 150-157Chapter in book (Other academic)
  • 41.
    Nouri, Jalal
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Cerratto-Pargman, Teresa
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    When Teaching Practices Meet Tablets’ Affordances: Insights on the Materiality of Learning2016In: Adaptive and Adaptable Learning: Proceedings / [ed] Katrien Verbert, Mike Sharples, Tomaž Klobučar, Springer, 2016, p. 179-192Conference paper (Refereed)
    Abstract [en]

    Research on tablets in schools is currently dominated by the effects these devices have on our children’s learning. Little has yet been said about how these devices contribute and participate in established school practices. This study delves into the questions of what do tablet-mediated teaching practices look like in Swedish schools and how are these practices valued by teachers? We collected data in four Swedish schools that were part of the one-to-one program financed by their municipalities. We apply qualitative and quantitative analysis methods on 22 deep interviews, 20 classrooms observations and 30 teachers’ responses to an online survey. The study identifies a set of tablet-mediated teaching practices that lead to a deeper understanding of how affordances of media tablets configure contemporary forms of learning.

  • 42.
    Nouri, Jalal
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Cerratto-Pargman, Teresa
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Eliasson, Johan
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Ramberg, Robert
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Exploring the challenges of supporting collaborative mobile learning2011In: International Journal of Mobile and Blended Learning, ISSN 1941-8647, E-ISSN 1941-8655, Vol. 3, no 4, p. 70-85Article in journal (Refereed)
    Abstract [en]

    Mobile technology opens up opportunities for collaborative learning in otherwise remote contexts outside the classroom. A successful realization of these opportunities relies, however, on mobile learning activities providing adequate collaboration structures. This article presents an empirical study aimed at examining the role played by mobile devices, teachers and task structures as a means for collaborative learning in geometry. The study focused on the analysis of the nature of collaboration that unfolded when students measured areas outdoors in the field. The analysis of the mobile learning activity was conducted from an Activity theory perspective. The findings obtained indicate that the collaboration observed may be impaired if: 1) the functionalities needed for collaborative problem-solving are asymmetrically distributed on a number of mobile devices; 2) task-related information is not accessible to all learners; 3) the task structure is not sufficiently complex; 4) teacher scaffolding is too readily available; and 5) necessary collaborative skills are not developed.

  • 43.
    Nouri, Jalal
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Cerratto-Pargman, Teresa
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Rossitto, Chiara
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Ramberg, Robert
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Learning with or without mobile devices? A comparison of traditional school field trips and inquiry-based mobile learning activities2014In: Research and Practice in Technology Enhanced Learning, ISSN 1793-7078, Vol. 9, no 2, p. 241-262Article in journal (Refereed)
  • 44.
    Nouri, Jalal
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Cerratto-Pargman, Teresa
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Zetali, Karwan
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Mobile inquiry-based Learning2013In: Human-Computer Interaction. Applications and Services: 15th International Conference, HCI International 2013. Proceedings Part II / [ed] Masaaki Kurosu, Springer Berlin/Heidelberg, 2013, p. 464-473Conference paper (Refereed)
    Abstract [en]

    This paper presents a study on mobile learning that could be viewed as a manifestation of strong voices calling for learning in natural contexts. The study was based on a sequence of inquiry-based mobile learning activities within the domain of natural sciences and mathematics education. We questioned the effects of collaborative scaffolding, and the effects scaffolding provided by technology have on learning and performance. Based on a quantitative interaction analysis, findings suggest that low-achievement students benefit from inquiry-based mobile activities; that the use of mobile technologies bring multiple effects on students’ learning, both positive and negative, and that the roles of teachers remains as crucial as before the introduction of learning technologies.

  • 45.
    Nouri, Jalal
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Cerratto-Pargman, Teresa
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Zetali, Karwan
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Multiple effects of collaborative mobile inquiry-based learning2013In: To See the World and a Grain of Sand: Learning across Levels of Space, Time, and Scale: CSCL 2013 Conference Proceedings Volume 2 — Short Papers, Panels, Posters, Demos, & Community Events / [ed] Nikol Rummel, Manu Kapur, Mitchell Nathan, Sadhana Puntambekar, International Society of the Learning Sciences, 2013, p. 323-324Conference paper (Refereed)
  • 46.
    Nouri, Jalal
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Ebner, Martin
    Ifenthaler, Dirk
    Saqr, Mohammed
    Malmberg, Jonna
    Khalil, Mohammad
    Bruun, Jesper
    Viberg, Olga
    Conde González, Miguel Ángel
    Papamitsiou, Zacharoula
    Berthelsen, Ulf Dalvad
    Efforts in Europe for Data-Driven Improvement of Education – A review of learning analytics research in seven countries2019In: International journal of learning analytics and artificial intelligence for education, ISSN 2706-7564, Vol. 1, no 1, p. 8-27Article in journal (Refereed)
    Abstract [en]

    Information and communication technologies are increasingly mediating learning and teaching practices as well as how educational institutions are handling their administrative work. As such, students and teachers are leaving large amounts of digital footprints and traces in various educational apps and learning management platforms, and educational administrators register various processes and outcomes in digital administrative systems. It is against such a background we in recent years have seen the emergence of the fast-growing and multi-disciplinary field of learning analytics. In this paper, we examine the research efforts that have been conducted in the field of learning analytics in Austria, Denmark, Finland, Norway, Germany, Spain, and Sweden. More specifically, we report on developed national policies, infrastructures and competence centers, as well as major research projects and developed research strands within the selected countries. The main conclusions of this paper are that the work of researchers around Europe has not led to national adoption or European level strategies for learning analytics. Furthermore, most countries have not established national policies for learners’ data or guidelines that govern the ethical usage of data in research or education. We also conclude, that learning analytics research on pre-university level to high extent have been overlooked. In the same vein, learning analytics has not received enough focus form national and European national bodies. Such funding is necessary for taking steps towards data-driven development of education.

  • 47.
    Nouri, Jalal
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Larsson, Ken
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Saqr, Mohammed
    University of Eastern Finland, Finland.
    Bachelor thesis analytics to understand and improve quality and performance2020In: Technology, Knowledge and Learning, ISSN 2211-1662, E-ISSN 2211-1670Article in journal (Refereed)
    Abstract [en]

    The bachelor thesis is commonly a necessary last step towards the first graduation in higher education and constitutes a central key to both further studies in higher education and employment that requires higher education degrees. Thus, completion of the thesis is a desirable outcome for individual students, academic institutions and society, and non-completion is a significant cost. Unfortunately, many academic institutions around the world experience that many thesis projects are not completed and that students struggle with the thesis process. This paper addresses this issue with the aim to, on the one hand, identify and explain why thesis projects are completed or not, and on the other hand, to predict non-completion and completion of thesis projects using machine learning algorithms. The sample for this study consisted of bachelor students’ thesis projects (n=2436) that have been started between 2010 and 2017. Data were extracted from two different data systems used to record data about thesis projects. From these systems, thesis project data were collected including variables related to both students and supervisors. Traditional statistical analysis (correlation tests, t-tests and factor analysis) was conducted in order to identify factors that influence non-completion and completion of thesis projects and several machine learning algorithms were applied in order to create a model that predicts completion and non-completion. When taking all the analysis mentioned above into account, it can be concluded with confidence that supervisors’ ability and experience play a significant role in determining the success of thesis projects, which, on the one hand, corroborates previous research.

    On the other hand, this study extends previous research by pointing out additional specific factors, such as the time supervisors take to complete thesis projects and the ratio of previously unfinished thesis projects. It can also be concluded that the academic title of the supervisor, which was one of the variables studied, did not constitute a factor for completing thesis projects. One of the more novel contributions of this study stems from the application of machine learning algorithms that were used in order to – reasonably accurately – predict thesis completion/non-completion. Such predictive models offer the opportunity to support a more optimal matching of students and supervisors.

  • 48.
    Nouri, Jalal
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Larsson, Ken
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Saqr, Mohammed
    Bachelor Thesis Analytics: Using Machine Learning to Predict Dropout and Identify Performance Factors2019In: International journal of learning analytics and artificial intelligence for education, ISSN 2706-7564, Vol. 1, no 1, p. 116-131Article in journal (Refereed)
    Abstract [en]

    The bachelor thesis is commonly a necessary last step towards the first graduation in higher education and constitutes a central key to both further studies in higher education and employment that requires higher education degrees. Thus, completion of the thesis is a desirable outcome for individual students, academic institutions and society, and non-completion is a significant cost. Unfortunately, many academic institutions around the world experience that many thesis projects are not completed and that students struggle with the thesis process. This paper addresses this issue with the aim to, on the one hand, identify and explain why thesis projects are completed or not, and on the other hand, to predict non-completion and completion of thesis projects using machine learning algorithms. The sample for this study consisted of bachelor students’ thesis projects (n=2436) that have been started between 2010 and 2017. Data were extracted from two different data systems used to record data about thesis projects. From these systems, thesis project data were collected including variables related to both students and supervisors. Traditional statistical analysis (correlation tests, t-tests and factor analysis) was conducted in order to identify factors that influence non-completion and completion of thesis projects and several machine learning algorithms were applied in order to create a model that predicts completion and non-completion. When taking all the analysis mentioned above into account, it can be concluded with confidence that supervisors’ ability and experience play a significant role in determining the success of thesis projects, which, on the one hand, corroborates previous research. On the other hand, this study extends previous research by pointing out additional specific factors, such as the time supervisors take to complete thesis projects and the ratio of previously unfinished thesis projects. It can also be concluded that the academic title of the supervisor, which was one of the variables studied, did not constitute a factor for completing thesis projects. One of the more novel contributions of this study stems from the application of machine learning algorithms that were used in order to – reasonably accurately – predict thesis completion/non-completion. Such predictive models offer the opportunity to support a more optimal matching of students and supervisors.

  • 49.
    Nouri, Jalal
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Larsson, Ken
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Saqr, Mohammed
    Identifying Factors for Master Thesis Completion and Non-completion Through Learning Analytics and Machine Learning2019In: Transforming Learning with Meaningful Technologies: Proceedings / [ed] Maren Scheffel, Julien Broisin, Viktoria Pammer-Schindler, Andri Ioannou, Jan Schneider, Springer, 2019, p. 28-39Conference paper (Refereed)
    Abstract [en]

    The master thesis is the last formal step in most universities around the world. However, all students do not finish their master thesis. Thus, it is reasonable to assume that the non-completion of the master thesis should be viewed as a substantial problem that requires serious attention and proactive planning. This learning analytics study aims to understand better factors that influence completion and non-completion of master thesis projects. More specifically, we ask: which student and supervisor factors influence completion and non-completion of master thesis? Can we predict completion and non-completion of master thesis using such variables in order to optimise the matching of supervisors and students? To answer the research questions, we extracted data about supervisors and students from two thesis management systems which record large amounts of data related to the thesis process. The sample used was 755 master thesis projects supervised by 109 teachers. By applying traditional statistical methods (descriptive statistics, correlation tests and independent sample t-tests), as well as machine learning algorithms, we identify five central factors that can accurately predict master thesis completion and non-completion. Besides the identified predictors that explain master thesis completion and non-completion, this study contributes to demonstrating how educational data and learning analytics can produce actionable data-driven insights. In this case, insights that can be utilised to inform and optimise how supervisors and students are matched and to stimulate targeted training and capacity building of supervisors.

  • 50.
    Nouri, Jalal
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Mozelius, Peter
    A framework for evaluating and orchestrating game-based learning that fosters computional thinking2018In: EDULEARN18: Proceedings, The International Academy of Technology, Education and Development, 2018, p. 1305-1310Conference paper (Refereed)
    Abstract [en]

    For some years now many teachers around the world have explored programming with their pupils in K-9 education. Research has shown that educational games of different kinds are often utilized by teachers as a mean for teaching programming and developing computational thinking among pupils. However, teaching and learning programming and computational thinking trough educational games is associated with a number of challenges. One of those challenges are related to that teachers are presented with an ever increasing amount of educational games and not supported with tools that, one the one hand, can help them evaluate the didactical affordances and potentials of specific games so they can select curriculum appropriate games, and on the other hand, that can help them design and orchestrate game-based learning activities. It is against such a background this paper presents a framework for the evaluation and orchestration of game-based learning activities that fosters computational thinking. The framework consists of two dimensions, namely game mechanics and learning mechanics. These two dimensions consists of a number of aspects that teachers and researchers can take into account in order to evaluate and design activities, and to reap the benefits of the didactical affordances of the games and the available scaffolding resources built inside games and available outside of them.

12 1 - 50 of 97
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