LA Unit Publications

2024

  1. M. Saqr, M.J. Schreuder, S. López-Pernas, Why educational research needs a complex system revolution that embraces individual differences, heterogeneity, and uncertainty. In Saqr, M., López-Pernas, S. (Eds.), Learning Analytics Methods and Tutorials. Springer, Cham, 2024.
  2. J. Jongerling, S. López-Pernas, M. Saqr, L.V.D.E. Vogelsmeier, Structural eqation modeling with R for educational scientists. In Saqr, M., López-Pernas, S. (Eds.), Learning Analytics Methods and Tutorials. Springer, Cham, 2024.
  3. L.V.D.E. Vogelsmeier, M. Saqr, S. López-Pernas, J. Jongerling, Factor analysis in education research using R. In Saqr, M., López-Pernas, S. (Eds.), Learning Analytics Methods and Tutorials. Springer, Cham, 2024.
  4. M. Saqr, E. Beck, S. López-Pernas, Psychological networks: A modern approach to analysis of lerning and complex learning processes. In Saqr, M., López-Pernas, S. (Eds.), Learning Analytics Methods and Tutorials. Springer, Cham, 2024.
  5. M. Saqr, Temporal network analysis: Introduction, methods and analysis with R. In Saqr, M., López-Pernas, S. (Eds.), Learning Analytics Methods and Tutorials. Springer, Cham, 2024.
  6. Á. Hernández-García, C. Cuenca-Enrique, A. Traxler, S. López-Pernas, M.Á. Conde-González, M. Saqr, Communicty detection in learning networks using R. In Saqr, M., López-Pernas, S. (Eds.), Learning Analytics Methods and Tutorials. Springer, Cham, 2024.
  7. M. Saqr, S. López-Pernas, M.Á. Conde-González, Á. Hernández-García, Social network analysis: A primer, a guide and a tutorial in R. In Saqr, M., López-Pernas, S. (Eds.), Learning Analytics Methods and Tutorials. Springer, Cham, 2024.
  8. S. López-Pernas, M. Saqr, The why, the how and the when of educational process mining in R. In Saqr, M., López-Pernas, S. (Eds.), Learning Analytics Methods and Tutorials. Springer, Cham, 2024.
  9. S. López-Pernas, M. Saqr, S. Helske, K. Murphy, Multi-channel sequence analysis in educational research: An introduction and tutorial with R. In Saqr, M., López-Pernas, S. (Eds.), Learning Analytics Methods and Tutorials. Springer, Cham, 2024.
  10. J. Helske, S. Helske, M. Saqr, S. López-Pernas, K. Murphy, A modern approach to transition analysis and process mining with Markov models in education. In Saqr, M., López-Pernas, S. (Eds.), Learning Analytics Methods and Tutorials. Springer, Cham, 2024.
  11. S. López-Pernas, M. Saqr, Modelling the dynamics of longitudinal process in education. A tutorial with R for the VaSSTra method. In Saqr, M., López-Pernas, S. (Eds.), Learning Analytics Methods and Tutorials. Springer, Cham, 2024.
  12. M. Saqr, S. López-Pernas, S. Helske, M. Durand, K. Murphy, M. Studer, G. Ritschard, Sequence analysis in education: Principles, techniques, and tutorial with R. In Saqr, M., López-Pernas, S. (Eds.), Learning Analytics Methods and Tutorials. Springer, Cham, 2024.
  13. L. Scrucca, M. Saqr, S. López-Pernas, K. Murphy, An introduction and R tutorial to model-based clustering in education via latent profile analysis. In Saqr, M., López-Pernas, S. (Eds.), Learning Analytics Methods and Tutorials. Springer, Cham, 2024.
  14. K. Murphy, S. López-Pernas, M. Saqr, Dissimilarity-based cluster analysis of educational data: A comperetive tutorial using R. In Saqr, M., López-Pernas, S. (Eds.), Learning Analytics Methods and Tutorials. Springer, Cham, 2024.
  15. J. Jovanovic, S. López-Pernas, M. Saqr, Predictive modelling in learning analytics: A machine learning approach in R. In Saqr, M., López-Pernas, S. (Eds.), Learning Analytics Methods and Tutorials. Springer, Cham, 2024.
  16. S. López-Pernas, K. Misiejuk, S. Tikka, J. Kopra, M. Heinäniemi, M. Saqr, Visualizing and reporting educational data with R. In Saqr, M., López-Pernas, S. (Eds.), Learning Analytics Methods and Tutorials. Springer, Cham, 2024.
  17. S. Tikka, J. Kopra, M. Heinäniemi, S. López-Pernas, M. Saqr, Introductory statistics with R for educational researchers. In Saqr, M., López-Pernas, S. (Eds.), Learning Analytics Methods and Tutorials. Springer, Cham, 2024.
  18. J Kopra, S. Tikka, M. Heinäniemi, S. López-Pernas, M. Saqr, An R approach to data cleaning and wrangling for education research. In Saqr, M., López-Pernas, S. (Eds.), Learning Analytics Methods and Tutorials. Springer, Cham, 2024.
  19. S. Tikka, J. Korpa, M. Heinäniemi, S. López-Pernas, M. Saqr, Getting started with R for educattion research. In Saqr, M., López-Pernas, S. (Eds.), Learning Analytics Methods and Tutorials. Springer, Cham, 2024.
  20. S. López-Pernas, M. Saqr, J. Conde, L. Del-Río-Carazo, A broad collection of datasets for educational research training and application. In Saqr, M., López-Pernas, S. (Eds.), Learning Analytics Methods and Tutorials. Springer, Cham, 2024.
  21. S. López-Pernas, K. Misiejuk, R. Kaliisa, M.Á, Conde-González, M. Saqr, Capturing the wealth and diversity of learning processes with learning analytics methods. In Saqr, M., López-Pernas, S. (Eds.), Learning Analytics Methods and Tutorials. Springer, Cham, 2024.
  22. M. Saqr, S. López-Pernas, Why learning and teaching learning analytics is hard: An experience from a real-life course using LA methods. In Gonçalves, J.A.d.C., Lima, J.L.S.d.M., Coelho, J.P., García-Peñalvo, F.J., García-Holgado, A. (Eds.), Proceedings of TEEM 2023. TEEM 2023. Lecture Notes in Educational Technology. Springer, Singapore, 2024.
  23. R. Elmoazen, M. Saqr, M. Tedre, L. Hirsto, Capturing the sequental pattern of students’ interactions in computer-supported collaborative learning. In Gonçalves, J.A.d.C., Lima, J.L.S.d.M., Coelho, J.P., García-Peñalvo, F.J., García-Holgado, A. (Eds.), Proceedings of TEEM 2023. TEEM 2023. Lecture Notes in Educational Technology. Springer, Singapore, 2024.
  24. S. López-Pernas, A. Gordillo, E. Barra, M. Saqr, The dynamics of students’ playing profiles in a programming educational escape room. In Gonçalves, J.A.d.C., Lima, J.L.S.d.M., Coelho, J.P., García-Peñalvo, F.J., García-Holgado, A. (Eds.), Proceedings of TEEM 2023. TEEM 2023. Lecture Notes in Educational Technology. Springer, Singapore, 2024.
  25. P. Rai, S. López-Pernas, R. Elmoazen, M. Saqr, More data is not always better data: An exploratory learning analytics study in early prediction. In Gonçalves, J.A.d.C., Lima, J.L.S.d.M., Coelho, J.P., García-Peñalvo, F.J., García-Holgado, A. (Eds.), Proceedings of TEEM 2023. TEEM 2023. Lecture Notes in Educational Technology. Springer, Singapore, 2024.
  26. K. Huhta, S. López-Pernas, M. Saqr, Mapping the topics, trends, and themes of educational technology in legal education with topic modelling and network analysis. In Gonçalves, J.A.d.C., Lima, J.L.S.d.M., Coelho, J.P., García-Peñalvo, F.J., García-Holgado, A. (Eds.), Proceedings of TEEM 2023. TEEM 2023. Lecture Notes in Educational Technology. Springer, Singapore, 2024.
  27. G. Akçapınar, E. Er, S. López-Pernas, M. Saqr, How a learning analytics dashboard intervention influences the dynamics of students’ learning behavior. In Gonçalves, J.A.d.C., Lima, J.L.S.d.M., Coelho, J.P., García-Peñalvo, F.J., García-Holgado, A. (Eds.), Proceedings of TEEM 2023. TEEM 2023. Lecture Notes in Educational Technology. Springer, Singapore, 2024.
  28. M. Saqr, L. Vogelsmeier, S. López-Pernas, Capturing where learning takes place: A person- specific and person-centered primer. Learning and Individual Differences, vol. 113, 2024.
  29. A. Santamaría Urbieta, S. López-Pernas, Hint strategies in educational escape rooms: a process mining approach. Revista De Educación, no. 1, pp. 13–38, 2024.
  30. N. Pope, H. Vartiainen, J. Kahila, J. Laru, M. Tedre, A no-code AI education tool for learning AI in K-12 by machine learning-driven apps. To apper in the Proceedings of the 24th International Conference on Learning Technologies, IEEE.
  31. S. Hamouda, L. Marshall, K. Sanders, E. Tshukudu, O. Adelakun-Adeyemo, B.A. Becker, E.R. Dodoo, G. Ayorkor Korsah, S. Luvhengo, O. Ola, J. Parkinson, I.T. Sanusi, Working group proposal: Computing education in Africa. Proceedings of the 2024 on Innovation and Technology in Computer Science Education V.2, pp. 755-756, ACM, 2024.
  32. I.T. Sanusi, E. Tshukudu, Exploring barriers and strategies to boost scientific output in computing education in Africa: Early insigths. Proceedings of the 2024 on Innovation and Technology in Computer Science Education V.1, pp. 736-743, ACM 2024.
  33. O.O. Campbell, I.T. Sanusi, H.I. Atagana, From visual arts to programming: Exploring the impact of achievement in constructionist college CS1 classes. Proceedings of the 2024 on Innovation and Technology in Computer Science Education V.1, pp. 604-610, ACM, 2024.
  34. C. Schulte, S. Sentance, S. Sparman, R. Altin, M. Friebrnoon-Yesharim, M. Landman, M.T. Rücker, S. Satavlekar, A. Siegel, M. Tedre, L. Tubino, H. Vartiainen, J.Ã. Velàzquez-Iturbide, J. Waite, Z. Wu, Values and beliefs underpinning K-12 computing education. Proceedings of the 2024 on Innovation and Technology in Computer Science Education V.2, pp. 767-768, ACM, 2024.
  35. M. Apiola, H. Vartiainen, M. Tedre, First year CS students exploring and identifying biases and social injustices in text-to-image generative AI. Proceedings of the 2024 on Innovation and Technology in Computer Science Education V.1, pp. 485-491, ACM, 2024.
  36. M. Saqr, R. Cheng, S. López-Pernas, E.D. Beck, Idiographic artificial intelligence to explain students’ self-regulation: Toward precision education. Learning and Individual Differences, vol. 114, 2024.
  37. J. Tyni, A. Turunen, R. Bednarik, J. Kahila, M. Tedre, Can ChaptGPT match experts: Comparing inputs for serius games development. International Journal of Serious Games, vol. 11, no. 2, pp. 87-106, 2024.
  38. E.-M. Zahn, S. Schöbel, M. Saqr, M. Söllner, Mapping soft skills and further research directions for higher education: a bibliometric approach with structural topic modelling. Studies in Higher Education, 2024.
  39. R. Kaliisa, S. López-Pernas, M. Saqr, C. Damsa, Exploring the dynamics and trends of knowledge exchange: A structured topic modelling approach of the CSCL conference. Proceedings of the 17th International Conference on Computer-Supported Collaborative Learning, The International Society of the Learning Sciences, 2024.
  40. F. Lin, R. Morland, H. Yan, QuizMaster: An adaptive formative assessment system. In Sifaleras, A., Lin, F. (Eds.) Generative Intelligence and Intelligent Tutoring Systems. ITS 2024. Lecture Notes in Computer Science, vol 14798. Springer, Cham, 2024.
  41. H. Yan, F. Lin, Kinshuk, An AI-learner shared control model for adaptive practicing. In Sifaleras, A., Lin, F. (Eds.) Generative Intelligence and Intelligent Tutoring Systems. ITS 2024. Lecture Notes in Computer Science, vol 14798. Springer, Cham, 2024.
  42. K. Mäkitalo, M. Tedre, J. Laru, T. Valtonen, M. Iwata, J. Koivisto, Learning computational thinking in co-creation projects with modern educational technology: Experiences from Finland. In Abelson, H., Kong, S.-C. (Eds.). Computational Thinking Curricula in K-12: International Implications. The MIT Press, 2024.
  43. Y. Albadarin, M. Saqr, N. Pope, M. Tukiainen, A systematic literature review of empirical research on ChatGPT in education. Discover Education, vol. 3, article number 60, 2024.
  44. F.G. Deriba, M. Saqr, M. Tukiainen, Assessment of accessbility in virtural laboratories: A systematic review. Frontiers in Education, 2024.
  45. M. Saqr, S. López-Pernas, K. Murphy, How group structure, members’ interactions and teacher facilitation explain the emergence of roles in collaborative learning. Learning and Individual Differences, vol. 112, 2024.
  46. H. Vartiainen, J. Kahila, M. Tedre, S. López-Pernas, N. Pope, Enhancing children’s understanding of algorithmic biases in and with text-to-image generative AI. New Media & Society, 2024.
  47. M. Saqr, S. S. López-Pernas (Eds.), Learning analytics methods and tutorials: A practical guide using R, Springer, In press.
  48. J. Conde, S. López-Pernas, E. Barra, M. Saqr, The temporal dynamics of procrastination and its impact on adademic performance: The case of a task-oriented programming course. The 39th ACM/SIGAPP Symposium on Applied Computing (SAC ’24), 2024.
  49. E. Sointu, S. Väisänen, L. Hirsto, T. Paavalainen, M. Saqr, S. López-Pernas, T. Valtonen, Creatively opening the constraints of learning analytics in inclusive, Elementary-School Level STEAM Education. In: Tillman, D.A. (Eds.) Exploring Perspectives on Creativity Theory and Research in Education. Creativity Theory and Action in Education, vol 8. Springer, Cham, 2024.
  50. I. Kilanioti, M. Saqr, M.Á. Queiruga-Dios, Editorial: Diversity in the social sciences: researching digital education in and for the global south. Frontiers in Education, vol.9, 2024.
  51. A. Munoz-Arcentales, J. Conde, Á. Alonzo, J. Salvachúa, W. Velasquez, S. López-Pernas, Data fusion and homogenization: Two key aspecrts for building digital twins of smart spaces. In: Liu, Z. (Eds.), Intelligent Data-Centric Systems, Smart Spaces. Academic Press, 2024.
  52. R. Kaliisa, K. Misiejuk, S. López-Pernas, M. Khalil, M. Saqr, Have learning analytics dashboards lived up the hype? A systematic review of impact on students’ achievement, motivation, participation and attitude. Proceedings of 14th Learning Analytics and Knowledge Conference, pp. 296-304, ACM, 2024.
  53. M. Saqr, S. López-Pernas, Mapping the self in self-regulation using complex dynamic systems approach. British Journal of Educational Technology, 2024.
  54. Saqr M. (2024). Group-level analysis of engagement poorly reflects individual students’ processes: Why we need idiographic learning analytics. Computers in Human Behavior, art. no. 107991. doi: 10.1016/j.chb.2023.107991.+
  55. Mertala P., López-Pernas S., Vartiainen H., Saqr M., Tedre M. (2024). Digital natives in the scientific literature: A topic modeling approach. Computers in Human Behavior, art. no. 108076. doi: 10.1016/j.chb.2023.108076.+
  56. Bobrowicz K., López-Pernas S., Teuber Z., Saqr M., Greiff S. (2024). Prospects in the field of learning and individual differences: Examining the past to forecast the future using bibliometrics. Learning and Individual Differences, art. no. 102399. doi: 10.1016/j.lindif.2023.102399.

2023

  1. K. Bobrowicz, S. López-Pernas, Z. Tauber, M. Saqr, S. Greiff, Prospects in the field of learning and individual differences: Examining the past to forecast the future using bibliometrics. Learning and Individual Differences, vol. 109, 2023.
  2. P. Mertala, S. López-Pernas, H. Vartiainen, M. Saqr, M. Tedre, Digital natives in the scientific literature: A topic modeling approach. Computers in Human Behavior, vol. 152, 2023.
  3. D. López-Fernández, A. Gordillo, S. López-Pernas, E. Tovar, Are remote educational escape rooms designed during the epidemic useful in a post-pandemic face-to-face setting?  IEEE Internet Computing, 2023.
  4. E. Barra, S. López-Pernas, A. Gordillo, A. Muñoz-Arcentales, J. Conde, Empowering database learning through remote educational escape rooms. IEEE Internet Computing, 2023.
  5. S. López-Pernas, Educational escape rooms are effective learning activities across educational levels and cotexts: Meta-analysis. IEEE Transactions on Learning Technologies, 2023.
  6. R. Klemola, S. López-Pernas, S. Väisänen, M. Saqr, E. Sointu, L. Hirsto, Learning analytics to explore the motivational profiles of non-traditional practical nurse students: A mixed methods approach. Empirical Research in Vocational and Education and Training, vol. 15, 2023.
  7. M. Saqr, Group-level analysis of engagement poorly reflects individual students’ processes: Why we need idiographic learning analytics. Computers in Human Behavior, 2023.
  8. M. Saqr, S. López-Pernas, L. Vogelsmeier, When, how and for whom changes in engagement happen: A transition analysis of instructional variables. Computers & Education, 2023.
  9. S. Hrastinski, S. Stenbom, M. Saqr, M. Jansson, O. Viberg, Examining the development of K-12 students’ cognitive presence over time: The case of online mathematics tutoring. Online Learning, vol. 27, no. 3, 2023.
  10. M. Saqr, W. Matcha, N.A. Uzir, J. Jovanovic, D. Gašević, S. López-Pernas, Transfering effective learning strategies across learning contexts matters: A study in problem-based learning. Australasian Journal of Educational Technology, 2023.
  11. S. López-Pernas, E. Barra, A. Gordillo, Á. Alonso, J. Quemada, Scaling student feedback in software engineering MOOCs. IEEE Software, In press.
  12. J. Kahila, T. Valtonen, S. López-Pernas, M. Saqr, H. Vartiainen, S. Kahila, M. Tedre, A typology of metagamers: Identifying player types based on beyond the game activities. Games and Culture, 2023.
  13. M.Á. Conde, A. Georgiev, S. López-Pernas, J. Jovic, I. Grespo-Martínez, M. R. Milic, M. Saqr, K. Pancehva, Definition of a learning analytics ecosystem for the IDELA project piloting. In: Zaphiris, P., Ioannou, A. (Eds.). Learning and Collaboration Technologies. HCII 2023. Lecture Notes in Computer Science, vol 14040. Springer, 2023.
  14. R. Elmoazen, S. López-Pernas, K. Misiejuk, M. Khalil, B. Wasson, M. Saqr, Reflections on technology-enhanced learning in laboratories: Barriers and opportunities. In Elmoazen, R., López-Pernas, S., Misiejuk, K., Khalil, M., Wasson, B., Saqr, M. (Eds.), Proceedings of the Technology-Enhanced Learning in Laboratories workshop (TELL 2023), CEUR-WS, 2023.
  15. F.G. Deriba, M. Saqr, M. Tukiainen, Exploring barriers and challenges to accessibility in virtual laboratories: a preliminary review. In Elmoazen, R., López-Pernas, S., Misiejuk, K., Khalil, M., Wasson, B., Saqr, M. (Eds.), Proceedings of the Technology-Enhanced Learning in Laboratories workshop (TELL 2023), CEUR-WS, 2023.
  16. L. Mairinoja, S. López-Pernas, R. Elmoazen, E.A. Niskanen, T. Kuningas, A. Wärri, M. Saqr, L. Strauss, International online team-based learning in higher education of biomedicine – evaluation by learning analytics. In Elmoazen, R., López-Pernas, S., Misiejuk, K., Khalil, M., Wasson, B., Saqr, M. (Eds.), Proceedings of the Technology-Enhanced Learning in Laboratories workshop (TELL 2023), CEUR-WS, 2023.
  17. S. López-Pernas, M. Saqr, From variables to states to trajectories (VaSSTra): A method for modelling the longitudinal dynamics of learning and behaviour. In: García-Peñalvo, F.J., García-Holgado, A. (Eds.), Proceedings TEEM 2022: Tenth International Conference on Technological Ecosystems for Enhancing Multiculturality. TEEM 2022. Lecture Notes in Educational Technology. Springer, Singapore, 2023.
  18. M.Á. Conde, S. López-Pernas, E. Peltekova, K. Pancheva, M. Raspopovic Milic, M. Saqr, Multi-stakeholder perspective on the gap between existing realities and new requirements for online and blended Learning: An exploratory study. In: García-Peñalvo, F.J., García-Holgado, A. (Eds.), Proceedings TEEM 2022: Tenth International Conference on Technological Ecosystems for Enhancing Multiculturality. TEEM 2022. Lecture Notes in Educational Technology. Springer, Singapore, 2023.
  19. E. Sointu, M. Saqr, T. Valtonen, S. Hallberg, S. Väisänen, J. Kankaanpää, V. Tuominen, L. Hirsto, (2023). SITE SPOTLIGHT ARTICLE: Understanding emotional behavior with learning analytics to support pre-service teachers’ learning in challenging content area. Journal of Technology and Teacher Education, 31(1), pp. 67-87, 2023.
  20. S. López-Pernas, R. Kleimola, S. Väisänen, L. Hirsto, Early detection of dropout factors in vocational education: A large-scale case study from Finland. In Hirsto, L., López-Pernas S., Saqr, M., Sointu, E., Valtonen, T. , Väisänen, S. (Eds.), Proceedings of the Finnish Learning Analytics and Artificial Intelligence in Education Conference (FLAIEC22). CEUR-WS, 2023.
  21. L. Hirsto, M. Saqr, S. López-Pernas, T. Valtonen, E. Sointu, S. Väisänen, Bridging education learning analytics and AI: Challenges of the present and thoughts for the future. In Hirsto, L., López-Pernas S., Saqr, M., Sointu, E., Valtonen, T. , Väisänen, S. (Eds.), Proceedings of the Finnish Learning Analytics and Artificial Intelligence in Education Conference (FLAIEC22). CEUR-WS, 2023.
  22. L. Hirsto, M. Saqr, S. López-Pernas, T. Valtonen, A systematic narrative review of learning analytics research in K-12 and schools. In Hirsto, L., López-Pernas S., Saqr, M., Sointu, E., Valtonen, T. , Väisänen, S. (Eds.), Proceedings of the Finnish Learning Analytics and Artificial Intelligence in Education Conference (FLAIEC22). CEUR-WS, 2023.
  23. S. Heikkinen, S. López-Pernas, J. Malmberg, M. Tedre, M. Saqr, How do business students self-regulate their project management learning? A sequence mining study. In Hirsto, L., López-Pernas S., Saqr, M., Sointu, E., Valtonen, T. , Väisänen, S. (Eds.), Proceedings of the Finnish Learning Analytics and Artificial Intelligence in Education Conference (FLAIEC22). CEUR-WS, 2023.
  24. M. Nissinen, E.Silvennoinen, M. Saqr, How assessment analytics can help to improve reliability, efficiency, and fairness of entrance examinations. In Hirsto, L., López-Pernas S., Saqr, M., Sointu, E., Valtonen, T. , Väisänen, S. (Eds.), Proceedings of the Finnish Learning Analytics and Artificial Intelligence in Education Conference (FLAIEC22). CEUR-WS, 2023.
  25. R. Elmoazen, M. Saqr, M. Tedre, L. Hirsto, How social interactions kindle productive online problem-based learning: An exploratory study of the temporal dynamics. In Hirsto, L., López-Pernas S., Saqr, M., Sointu, E., Valtonen, T. , Väisänen, S. (Eds.), Proceedings of the Finnish Learning Analytics and Artificial Intelligence in Education Conference (FLAIEC22). CEUR-WS, 2023.
  26. S. Schöbel, A. Schmitt, D. Benner, M. Saqr, A. Janson, J.M. Leimester, Charting the evolution and future of conversational agents: A research agenda along five waves and new frontiers. Information Systems Frontiers, 2023.
  27. B.A. Becker, S. Bradley, J. Maguire, M. Black, T. Crick, M. Saqr, S. Sentance, K. Quille, Computing education research in the UK & Ireland. In: Apiola, M., López-Pernas, S., Saqr, M. (Eds.). Past, Present and Future of Computing Education Research. Springer, Cham, 2023.
  28. V. Dagiené, Y. Gülbahar, N. Grgunia, S. López-Pernas, M. Saqr, M. Apiola, G. Stupuriené, Computing education research in schools. In: Apiola, M., López-Pernas, S., Saqr, M. (Eds.). Past, Present and Future of Computing Education Research. Springer, Cham, 2023.
  29. F.J. Agbo, M. Ntinda, S. López-Pernas, M. Saqr, M. Apiola, Computing education research in the global south. In: Apiola, M., López-Pernas, S., Saqr, M. (Eds.). Past, Present and Future of Computing Education Research. Springer, Cham, 2023.
  30. M. Apiola, S. López-Pernas, M. Saqr, L. Malmi, M. Daniels, Exploring the past, present and future of computing education research: An introduction. In: Apiola, M., López-Pernas, S., Saqr, M. (Eds.) Past, Present and Future of Computing Education Research. Springer, Cham, 2023.
  31. M. Saqr, S. López-Pernas, S. Helse, S. Hrastinski, The longitudinal association between engagement and achievement varies by time, students’ subgroups, and achievement state: A full program study. Computers & Education, 2023.
  32. M. Saqr, M.R. Milic, K. Pancheva, J. Jovic, E.V. Peltekova, M.Á. Conde, A multimethod synthesis of Covid-19 education research: the tightrope between covidization and meaningfulness. Universal Access in the Information Society, 2023.
  33. M. Saqr, S. López-Pernas, The temporal dynamics of online problem-based learning: Why and when sequence matters. International Journal of Computer-Supported Collaborative Learning, 2023.
  34. R. Elmoazen, M. Saqr, M. Khalil, B. Wasson, Learning analytics in virtual laboratories: A systematic literature review of empirical research. Smart Learning Environments, 2023.
  35. M. Saqr, Modelling within-person idiographic variance could help explain and individualize learning. British Journal of Educational Technology, 2023.’
  36. M. Saqr, S. López-Pernas, M. Apiola, Computing education research in social media, news, blogs, patents and blogs: Capturing the impact and the chatter with altmetrics. In: Apiola, M., López-Pernas, S., Saqr, M. (Eds.). Past, Present and Future of Computing Education Research: A Global Perspective, Springer, In press.
  37. M. Saqr, S. López-Pernas, J. Jovanovic, D. Gaševic, Intense, turbulent, or wallowing in the mire: A longitudinal study of cross-course online tactics, strategies, and trajectories. The Internet and Higher Education, vol. 57, 2023.
  38. M. Apiola, S. López-Pernas, M. Saqr, The hands that made computing education research: Top authors, networks, collaboration and newcomers. In: Apiola, M., López-Pernas, S., Saqr, M. (Eds.). Past, Present and Future of Computing Education Research: A Global Perspective, Springer, In press.
  39. S. López-Pernas, M. Saqr, M. Apiola, Scientometrics: A concise introduction and a detailed methodology for the mapping of the scientific field of computing education. In: Apiola, M., López-Pernas, S., Saqr, M. (Eds.). Past, Present and Future of Computing Education Research: A Global Perspective, Springer, In press.
  40. S. López-Pernas, M. Apiola, M.Saqr, A. Pears, M. Tedre, A scientometric perspective on the evolution of the SIGCSE Technical Symposium: 1970-2021. In: Apiola, M., López-Pernas, S., Saqr, M. (Eds.). Past, Present and Future of Computing Education Research: A Global Perspective, Springer, In press.
  41. L. Malmi, A. Hellas, P. Ihantola, V. Isomöttönen, I. Jormanainen, T. Kilamo, A. Knutas, A. Korhonen, M.-J. Laakso, S. López-Pernas, T. Poranen, T. Salakoski, J. Suhonen, Computing education research in Finland. In: Apiola, M., López-Pernas, S., Saqr, M. (Eds.). Past, Present and Future of Computing Education Research: A Global Perspective, Springer, In press.
  42. M. Apiola, S. López-Pernas, M. Saqr, The evolving themes of computing education research: Trends, topic models, and emerging research. In: Apiola, M., López-Pernas, S., Saqr, M. (Eds.). Past, Present and Future of Computing Education Research: A Global Perspective, Springer, In press.
  43. H. Vartiainen, S. López-Pernas, M. Saqr, J. Kahila, M. Tedre, T. Valtonen, Mapping students’ temporal pathways in a computational thinking escape room. In Hirsto, L., López-Pernas S., Saqr, M., Sointu, E., Valtonen, T. , Väisänen, S. (Eds.), Proceedings of the Finnish Learning Analytics and Artificial Intelligence in Education Conference (FLAIEC22). CEUR-WS, In press.

2022

  1. M. Saqr, S. López-Pernas, A. Hernández-García, M.Á., Conde, O. Poquet, Networks and learning analytics: Addressing educational challenges. In Proceedings of NetSciLA22: Networks and Learning Analytics: Addressing Educational Challenges, 2022.
  2. M. Saqr, S. López-Pernas, A. Hernández-García, Concluding remarks of the NetSciLA22 workshop. In Proceedings of NetSciLA22: Networks and Learning Analytics: Addressing Educational Challenges, 2022.
  3. M. Saqr, Is GPDR failing? a tale of the many challenges in interpretations, applications, and enforcement. International Journal of Health Sciences, vol. 16, no. 5, pp. 1-2, 2022.
  4. M. Saqr, V. Tuominen, T. Valtonen, E. Sointu, S. Väisänen, L. Hirsto, Teachers’ learning profiles in learning programming: The big picture!, Frontiers in Education, 2022.
  5. M. Saqr, S. López-Pernas, The why, the what and the how to model a dynamic relational learning process with temporal networks. In Proceedings of the NetSciLA 2022 Worskhop, 2022.
  6. S. López-Pernas, A. Munoz-Arcentales, C. Aparicio, E. Barra, A. Gordillo, J. Salvachua, J. Quemada, Educational data virtual lab: Connecting the dots between data visualization and analysis. IEEE Computer Graphics and Applications, vol. 42, no. 5, pp. 76-83, 2022.
  7. J. Malmberg, M. Saqr, H. Järvenoja, E. Haataja, Pijeira-Díaz, H.J., S. Järvelä, Modelling the complex interplay between monitoring events for regulated learning with psychological networks. In: Giannakos, M., Spikol, D., Di Mitri, D., Sharma, K., Ochoa, X., Hammad, R. (eds), The Multimodal Learning Analytics Handbook, pp. 79-104, Springer, Cham, 2022.
  8. J. Merikko, K. Ng, M. Saqr, P. Ihantola, To opt in or to opt out? Predicting student preferences for learning analytics-based formative feedback. IEEE Access, vol. 10, pp. 99195-99204, 2022.
  9. M. Saqr, S. López-Pernas, Instant or distant: A temporal network tale of two interaction platforms and their influence on collaboration. In: Hilliger, I., Muñoz-Merino, P.J., De Laet, T., Ortega-Arranz, A., Farrell, T. (Eds.) Educating for a New Future: Making Sense of Technology-Enhanced Learning Adoption. EC-TEL 2022. Lecture Notes in Computer Science, vol 13450. Springer, Cham, 2022.
  10. S. Heikkinen, M. Saqr, J. Malmberg, M. Tedre, Supporting self-regulated learning with learning analytics interventions – a systematic literature review. Education and Information Technologies, In press.
  11. M. Apiola, S. López-Pernas, M. Saqr, A. Pears, M. Daniels, L. Malmi, M. Tedre, From a national meeting to an international conference: A scientometric case study of a Finnish computing education conference. IEEE Access, vol. 10, pp. 66576-66588, 2022.
  12. T. Törmänen, H. Järvenoja, M. Saqr, J. Malmberg, S. Järvelä, Affective states and regulation of learning during socio-emotional interactions in secondary school collaborative groups. British Journal of Educational Psychology, 2022.
  13. E. Sointu, T. Valtonen, S. Hallberg, J. Kankaanpää, S. Väisänen, L. Heikkinen, M. Saqr, V. Tuominen, L. Hirsto, Learning analytics and flipped learning in online teaching for supporting preservice teachers’ learning of quantitative methods. Seminar.net, vol. 18, no.1, 2022.
  14. M. Saqr, S. López-Pernas, How CSCL roles emerge, persist, transition, and evolve over time: A four-year longitudinal study. Computers & Education, vol. 189, 2022.
  15. T. Törmänen, H. Järvenoja, M. Saqr, J. Malmberg, S. Järvelä, A person-centered approach to study students’ socio-emotional interaction profiles and regulation of collaborative learning. Frontiers in Education, vol. 7, 2022.
  16. L. Hirsto, T. Valtonen, M. Saqr, S. Hallberg, E. Sointu, J. Kankaanpää, S. Väisänen, Pupils’ experiences of utilizing learning analytics to support self-regulated learning in two phenomenon-based study modules. In E. Langran (Ed.), Proceedings of Society for Information Technology & Teacher Education International Conference 2022 (pp. 1682-1688). Waynesville, NC USA: Association for the Advancement of Computing in Education (AACE), 2022.
  17. E. Sointu, M. Saqr, T. Valtonen, S. Hallberg, S. Väisänen, J. Kankaanpää, V. Tuominen, L. Hirsto, Emotional behavior in quantitative research methods course for preservice teachers. Learning analytics approach. In E. Langran (Ed.), Proceedings of Society for Information Technology & Teacher Education International Conference 2022 (pp. 1880-1889). Waynesville, NC USA: Association for the Advancement of Computing in Education (AACE), 2022.
  18. M. Saqr, Jovanovic, J., O. Viberg, D. Gašević, Is there order in the mess? A single paper meta-analysis of approach to identification of predictors of success in learning analytics. Studies in Higher Education, 2022.
  19. J. Tyni, A. Tarkiainen, S. López-Pernas, M. Saqr, J. Kahila, R. Bednarik, M. Tedre, Games and rewards: A scientometric study of rewards in educational and serious games. IEEE Access, 2022.
  20. M. Saqr, O. Poquet, S. López-Pernas, Networks in education: A travelogue through five decades. IEEE Access, 2022.
  21. M. Saqr, S. López-Pernas, The curious case of centrality measures: A large-scale empirical investigation. Journal of Learning Analytics, vol. 9, no. 1, 13-31, 2022.
  22. J. Malmberg, M. Saqr, H. Järvenoja, S. Järvelä, How the monitoring events of individual students are associated with phases of regulation. Journal of Learning Analytics, vol. 9, no. 1, 77-92, 2022.
  23. O. Viberg, L. Engström, M. Saqr, S. Hrastinski, Exploring students’ expectations of learning analytics: A person-centered approach. Education and Information Technologies, 2022.
  24. M. Apiola, M. Saqr, S. López-Pernas, M. Tedre, Computing education research complied: Keyword trends, building blocks, creators, and dissemination. IEEE Access, 2022.
  25. I.I. Ismail, M. Saqr, A quantitative synthesis of eight decades of global multiple sclerosis research using bibliometrics. Frontiers in Neurology, In press.
  26. S. López-Pernas, M. Saqr, A. Gordillo, E. Barra, A learning analytics perspective on educational escape rooms. Interactive Learning Environments, 2022.
  27. M. Saqr, W. Peeters, Temporal networks in collaborative learning: A case study. British Journal of Educational Technology, 2022.
  28. R. Elmoazen, M. Saqr, M. Tedre, L. Hirsto, A systematic literature review of empirical research on epistemic network analysis in education. IEEE Access, 2022.
  29. M. Saqr, R. Elmoazen, M. Tedre, S. López-Pernas, L. Hirsto, How well centrality measures capture student achievement in computer-supported collaborative learning? – A systematic review and meta-analysis. Educational Research Review, vol. 35, 2022.
  30. M. Saqr, S. López-Pernas, The curious case of centrality measures: A large-scale empirical investigation. Journal of Learning Analytics, In press.
  31. M. Nissinen, E. Silvennoinen, M. Saqr, Monivalintakysymykset oikeustieteellisen alan yhteisvalintakokeessa – Hitti vai huti? Edilex, 2022.

2021

  1. Ofir, Z., Tedre, M. Saqr, M.,  Kliukina, S. End of programme evaluation of Sida’s support to the World Academy of Science (TWAS), 2017-2021.
  2. López-Pernas, S., M. Saqr, Bringing synchrony and clarity to complex multi-channel data: A learning analytic study in programming education. IEEE Access, vol.9, pp. 166531-166541, 2021.
  3. M. Saqr, S. López-Pernas, Modelling diffusion in computer-supported collaborative learning: A large scale learning analytics study. International Journal of Computer-Supported Collaborative Learning, 2021.
  4. T. Valtonen, S. López-Pernas, M. Saqr, H. Vartiainen, E.T. Sointu, M. Tedre, The nature and building blocks of educational technology research. Computers in Human Behavior, vol. 128, 2021.
  5. M. Apiola, M. Tedre, S. Lòpez-Pernas, M. Saqr, M. Daniels, A. Pears, A scientometric journey through the FIE bookshelf: 1982-2020. Proceedings of the 2021 IEEE Frontiers in Education (FIE) Conference, IEEE, 2021.
  6. M. Apiola, M. Tedre, S. Lòpez-Pernas, M. Saqr, M. Daniels, A. Pears, A scientometric journey through the FIE bookshelf: 1982-2020. Proceedings of the 2021 IEEE Frontiers in Education (FIE) Conference, IEEE, 2021.
  7. M. Saqr, S. López-Pernas, The dire cost of early disengagement: A four-year learning analytics study over a full program. In De Laet T., Klemke R., Alario-Hoyos C., Hilliger I., Ortega-Arranz A. (eds), Technology-Enhanced Learning for a Free, Safe, and Sustainable World. EC-TEL 2021. Lecture Notes in Computer Science, vol 12884. Springer, Cham, 2021.
  8. M. Saqr, S. López-Pernas, The longitudinal trajectories of online engagement over a full program. Computers & Education, vol. 175, 2021.
  9. M. Saqr, S. López-Pernas, Towards self-big data. International Journal of Health Sciences, vol. 15, no. 5, pp. 1-2, 2021.
  10. M. Saqr, S. López-Pernas, Idiographic learning analytics: A definition and case study. Proceedings of the 2021 International Conference on Advanced Learning Technologies (pp. 163-165), 2021
  11. S. Schöbel, M. Saqr, A. Janson, Two decades of game concepts in digital learning environments – A bibliometric study and research agenda. Computers & Education, 2021.
  12. M. Bermo, M. Saqr, H. Hoffman, D. Patterson, S. Sharar, S. Minoshima, D.H. Lewis, Utility of SPECT functional neuroimaging of brain. Frontiers in Psychiatry, 2021.
  13. J. Jovanović, M. Saqr, S. Joksimović, D. Gašević, Students matter the most in learning analytics: The effect of internal and instructional conditions in predicting academic success. Computers & Education, vol. 172, 2021.
  14. O. Poquet, B. Chen, M. Saqr, T. Hecking, Using network science in learning analytics: Building bridges towards a common agenda. Proceedings of the NetSciLA21 workshop, 2021.
  15. O. Poquet, M. Saqr, B. Chen, Recommendations for network research in learning analytics: To open a conversation. Proceedings of the NetSciLA21 workshop, 2021.
  16. S. López-Pernas, M. Saqr, O. Viberg, Putting it all together: Combining learning analytics methods and data sources to understand students’ approaches to learning programming. Sustainability, vol. 13, no. 9, 2021.
  17. M. Saqr, O. Viberg, W. Peeters, Using psychological networks to reveal the interplay between foreign language students’ self-regulated learning tactics. Proceedings of the 2020 STELLA Symposium, 2021
  18. M. Saqr, S. López-Pernas, Idiographic learning analytics: A single student (N=1) approach. Companion Proceedings of the 11th International Conference on Learning Analytics & Knowledge (LAK21), 2021.
  19. M. Saqr, K. Ng, S.S. Oyelere, M. Tedre, People, ideas, milestones: A scientometric analysis of computational thinking. ACM Transactions on Computing Education, vol. 21, no. 3, 2021.
  20. M. Saqr, J. Nouri, U. Fors, O. Viberg, M. Alsuhaibani, A. Alharbi, M. Alharbi, A. Alamer, How networking and social capital influence performance: The role of long-term ties. In Antonyuk A., Basov N. (eds.) Networks in the Global World V. Net Glow 2020. Lecture Notes in Networks and Systems, vol. 181. Springer, Cham, 2021.
  21. M. Wedberg, O. Viberg, M. Saqr, Facilitating disciplinary-specific knowledge sharing: A usability study of a dementia library. In Proceedings of the 19 World Conference on Mobile, Blended and Seamless Learning, 2021.

2020

  1. M. Saqr, O. Viberg, “Using diffusion network analysis to examine and support knowledge construction in CSCL settings“, In Alario-Hoyos C., Rodríguez-Triana M., Scheffel M., Arnedillo-Sánchez I., Dennerlein S. (Eds.) Addressing Global Challenges and Quality Education. EC-TEL 2020. Lecture Notes in Computer Science, vol 12315. Springer, Cham, 2020.
  2. M. Saqr, J. Nouri, H. Vartiainen, M. Tedre, “Robustness and rich clubs in collaborative learning groups: A learning analytics study using network science“, Scientific Reports, vol. 10, 2020.
  3. M. Saqr, A. Al-Mohaimeed, Z. Rasheed, “Tear down the walls: Disseminating open access research for a global impact“, International Journal of Health Sciences, vol. 15, no. 5, 2020.
  4. M. Saqr, O. Viberg, H. Vartiainen, “Capturing the participation and social dimensions of computer-supported collaborative learning through social network analysis: which method and measures matter?“,  International Journal of Computer-Supported Collaborative Learning, 2020.
  5. S. Schöbel, A. Janson, K. Jahn, B. Kordyaka, O. Turetken, N. Djafarova, M. Saqr, D. Wu, M. Söllner, M. Adam, P.H. Gap, H. Wesseloh, J.M. Leimeister, “A research agenda for why, what, and how of gamifications designs: Outcomes of an ECIS 2019 panel“, Communications of the Association for Information Systems, vol. 46, 2020.
  6. M. Saqr, B. Wasson, “COVID-19: Lost opportunities and lessons for the future“, International Journal of Health Sciences, vol. 14, no. 3, 2020.
  7. M. Saqr, J. Nouri, H. Vartiainen, J. Malmberg, “What makes an online problem-based group successful? A learning analytics study using social network analysis”, BMC Medical Education, vol. 20, no. 1, 2020.
  8. M. Saqr, C. Suero Montero, “Learning and social networks – similarities, differences and impact“, Proceedings of the IEEE 20th International Conference on Advanced Learning Technologies (ICALT2020), IEEE, 2020.
  9. M. Saqr, J. Nouri, “High resolution temporal network analysis to understand and improve collaborative learning“, In Proceedings of the 10th International Conference on Learning Analytics and Knowledge (LAK20), ACM, 2020.
  10. M. Saqr, O. Viberg, J. Nouri, S.S. Oyelere, “Multimodal temporal network analysis to improve learner support and teaching“, In Proceedings of CrossMMLA in Practice: Collecting, Annotating and Analyzing Multimodal Data Across Spaces Co-located with 10th International Learning and Analytics Conference (LAK 2020), 2020.

2019

  1. Nouri, J., Saqr, M., Fors, U., “Predicting performance of students in a flipped classroom using machine learning: towards automated data-driven formative feedback“, Journal of Systemics, Cybernetics and Informatics, vol. 17, no. 2, 17-21.
  2. Alsuhaibani, M., Alharbi, A., Inam S.N.B., Alarmo, A., Saqr, M. “Research education in an undergraduate curriculum: Students perspective“, International Journal of Health Sciences, vol. 13, no. 2, 30-34, 2019.
  3. J. Nouri, K. Larsson, M. Saqr, “Identifying factors for master thesis completion and non-completion through learning analytics and machine learning“, In Scheffel M., Broisin J., Pammer-Schindler V., Ioannou A., Schneider J. (Eds.), Transforming Learning with Meaningful Technologies. EC-TEL 2019. Lecture Notes in Computer Science, vol 11722. Springer, Cham, 2019.
  4. M. Saqr, J. Nouri, I. Jormanainen, “A learning analytics study of the effect of group size on social dynamics and performance in online collaborative learning“, In Scheffel M., Broisin J., Pammer-Schindler V., Ioannou A., Schneider J. (Eds.), Transforming Learning with Meaningful Technologies. EC-TEL 2019. Lecture Notes in Computer Science, vol 11722. Springer, Cham, 2019.
  5. J. Nouri, K. Larsson, M. Saqr, “Bachelor thesis analysis: Using machine learning to predict dropout and identify performance factors“, International Journal of Learning Analytics and Artificial Intelligence for Education, vol. 1, no.1, 2019.
  6. J. Nouri, M. Ebner, D. Ifenthaler, M. Saqr, J. Malmberg, M. Khalil, J. Bruun, O. Viberg, M. González, Z. Papamitsiou, U. D. Berthelsen, “Efforts in Europe for data-driven improvement of education – A review of learning analytics research in six countries“, International Journal of Learning Analytics and Artificial Intelligence for Education, vol. 1, no.1, 2019.
  7. M. Saqr, M. Tedre, “Should we teach computational thinking and big data principles to medical students?”, International Journal of Health Sciences, vol. 13, no. 4, 2019. https://ijhs.org.sa/index.php/journal/article/view/4310
  8. M. Saqr, A. Alamro, “The role of social network analysis as a learning analytic tool in online problem based learning“, BMC Medical Education, vol. 19, 2019.

2017-2018

  1. M. Saqr, U. Fors, M. Tedre, J. Nouri, “How social network analysis can be used to monitor online collaborative learning and guide an informed intervention”. PLoS ONE, vol. 13, no. 3, 2018. https://doi.org/10.1371/journal.pone.0194777
  2. M. Saqr, U. Fors, M. Tedre, “How the study of online collaborative learning can guide teachers and predict students’ performance in a medical course”. BMC Medical Education, vol. 18, no.24, 2018. https://bmcmededuc.biomedcentral.com/articles/10.1186/s12909-018-1126-1
  3. M. Saqr, U. Forst, M. Tedre, “How learning analytics can early predict under-achieving students in a blended medical education course”, Medical Teacher, vol. 39, no. 7., 2017. https://doi.org/10.1080/0142159X.2017.1309376