Artificial Intelligence for Learning Analytics and Instructional Design Steps: An Overview of Solutions

Keywords: artificial intelligence, learning analytics, instructional design, learning design, ADDIE, recommender systems, higher education


Artificial intelligence methods are getting frequently used in research and development in learning analytics, which is aimed at analyzing data collected during learning to enhance its results. The same aim is relevant for instructional design models, the most widely applied is ADDIE model, which cuts course design into steps. The first two research fields are criticized for a weak connection to teaching practice, while the third lacks evidence-based and measurable nature. This literature review aims to show the prospects of bringing the three fields together. The theoretical analysis of the paper covers AI definition, its techniques and methods, areas of application in educational setting, the definition of learning analytics, its borders with other fields, spheres of application, definition and the essence of instructional design, as well as the concept of ADDIE model which frames the practical analysis of the review. Forty-three articles were included in the final sample. The solutions described there correlate with the tasks of the instructional design steps and are systematized according to them. It was found that the least number of solutions described in the literature were assigned to the analysis, design and evaluation steps, more articles were assigned to the development step, and the largest number of papers considered the application step. It can be due to the difference in the availability of data at different ADDIE steps. The weak focus of teachers on methodological reflection at the assessment step also may play a role. These deficiencies open up the opportunities for future research and developments. To push these solutions forward it is crucial to elaborate on the models, to move from anecdotal experiments to a wide-scale practice, and to enhance required competencies among the faculty. The questions and conclusions presented in the article help to set a new pedagogically-oriented framework for discussions of AI and learning data analytics.


Download data is not yet available.


Abdelhakim M.N.A., Shirmohammadi S. (2008) Improving Educational Multimedia Selection Process Using Group Decision Support Systems. International Journal of Advanced Media and Communication, vol. 2, no 2, pp. 174–190.

Abu-Dalbouh H.M. (2021) Application of Decision Tree Algorithm for Predicting Students’ Performance via Online Learning during Coronavirus Pandemic. Journal of Theoretical and Applied Information Technology, vol. 99, no 19, pp. 4546–4556.

Afridi A.H. (2019) Transparency for Beyond-Accuracy Experiences: A Novel User Interface for Recommender Systems. Procedia Computer Science, no 151, pp. 335–344.

Afridi A.H. (2018) Stakeholders Analysis for Serendipitous Recommenders System in Learning Environments. Procedia Computer Science, no 130, pp. 222–230.

Aldowah H., Al-Samarraie H., Fauzy W.M. (2019) Educational Data Mining and Learning Analytics for 21st Century Higher Education: A Review and Synthesis. Telematics and Informatics, vol. 37, April, pp. 13–49.

Anaya A.R., Luque M., Peinado M. (2016) A Visual Recommender Tool in a Collaborative Learning Experience. Expert Systems with Applications, vol. 45, October, pp. 248–259.

Asli M. F., Hamzah M., Ibrahim A.A.A., Ayub E. (2020) Problem Characterization for Visual Analytics in MOOC Learner's Support Monitoring: A Case of Malaysian MOOC. Heliyon, vol. 6, no 12, Article no e05733.

Baker R.S. (2021) Artificial Intelligence in Education: Bringing It All Together. OECD Digital Education Outlook 2021: Pushing the Frontiers with Artificial Intelligence, Blockchain and Robots. Paris: OECD, pp. 43–56.

Baker R.S., Inventado P.S. (2014) Educational Data Mining and Learning Analytics. Learning Analytics (eds J. Larusson, B. White), New York, NY: Springer, pp. 61–75.

Baker R.S.J.D., Yacef K. (2009) The State of Educational Data Mining in 2009: A Review and Future Visions. Journal of Educational Data Mining, vol. 1, no 1, pp. 3–17.

Branch R.M. (2009) Instructional Design: The ADDIE Approach. New York NY: Springer Science & Business Media.

Cabrera I., Villalon J. (2013) An Adaptive Interface for Computer-Assisted Rubrics in an E-Marking Tool Using Nearest Neighbor. Paper presented at International Conference on Advanced Learning Technologies (Beijing, China, 2013, 15–18 July)

Carchiolo V., Longheu A., Malgeri M. (2010) Reliable Peers and Useful Resources: Searching for the Best Personalised Learning Path in a Trust- and Recommendation-Aware Environment. Information Sciences, vol. 180, no 10, pp. 1893–1907.

Chan P., van Gerven T., Dubois J-L., Bernaerts K. (2021) Virtual Chemical Laboratories: A Systematic Literature Review of Research, Technologies and Instructional Design. Computers and Education Open, vol. 2, December, Article no 100053.

Chassignol M., Khoroshavin A., Klimova A., Bilyatdinova A. (2018) Artificial Intelligence Trends in Education: A Narrative Overview. Procedia Computer Science, vol. 136, January, pp. 16–24.

Chen Y.-C., Chang Y.-S., Chuang M.-J. (2022) Virtual Reality Application Influences Cognitive Load-Mediated Creativity Components and Creative Performance in Engineering Design. Journal of Computer Assisted Learning, vol. 38, no 1, pp. 6–18.

Chen Z., Xu M., Hu Z., Zhang S., Zhang J., Jiang X., Jumani A.K. (2021) Multimedia Educational System and Its Improvement Using AI Model for a Higher Education Platform. Journal of Multiple-Valued Logic and Soft Computing, vol. 36, no 1, pp. 25–41.

Clow D. (2013) An Overview of Learning Analytics. Teaching in Higher Education, vol. 18, no 6, pp. 683–695.

Cobos С., Rodriguez O., Rivera J., Betancourt J., Mendoza M., Leon E., Herrera-Viedma E. (2013) A Hybrid System of Pedagogical Pattern Recommendations Based on Singular Value Decomposition and Variable Data Attributes. Information Processing & Management, vol. 49, no 3, pp. 607–625.

Conole G. (2012) Designing for Learning in an Open World. New York NY: Springer Science & Business Media.

Corrin L., Kennedy G., de Barba P.G., Lockyer L. et al. (2016) Completing the Loop: Returning Meaningful Learning Analytic Data to Teachers. A Handbook for Educators and Learning Analytics Specialists. Sydney, NSW, Australia: Government of Australia Office for Learning and Teaching.

Cung B., Xu D., Eichhorn S., Warschauer M. (2019) Getting Academically Underprepared Students Ready through College Developmental Education: Does the Course Delivery Format Matter? American Journal of Distance Education, vol. 33, no 4, pp. 178–194.

De Medio C., Limongelli C., Sciarrone F., Temperini M. (2020) MoodleREC: A Recommendation System for Creating Courses Using the Moodle e-Learning Platform. Computers in Human Behavior, Vol. 104, Article no 106168.

Deng L., Yu D. (2014) Deep Learning: Methods and Applications. Foundations and Trends in Signal Processing, vol. 7, no 3-4, pp. 197–387.

Deo R.C., Yaseen Z.M., Al-Ansari N., Nguyen-Huy T., Mcpherson Langlands T.A, Galligan L. (2020) Modern Artificial Intelligence Model Development for Undergraduate Student Performance Prediction: An Investigation on Engineering Mathematics Courses. IEEE Access, vol. 8, July, pp. 136697–136724.

Dias S.B., Hadjileontiadou S.J., Hadjileontiadis L.J., Diniz J.A. (2015) Fuzzy Cognitive Mapping of LMS Users’ Quality of Interaction within Higher Education Blended-Learning Environment. Expert Systems with Applications, vol. 42, iss. 21, pp. 7399–7423.

Drljača D., Latinović B., Stanković Z., Cvetković D. (2017) ADDIE Model for Development of E-Courses. Proceedings of the Sinteza 2017 — International Scientific Conference on Information Technology and Data Related Research (Belgrade, 2017, 21 April), pp. 242–247.

Doleck T., Lemay D.J., Basnet R.B., Bazelais P. (2019) Predictive Analytics in Education: A Comparison of Deep Learning Frameworks. Education and Information Technologies, vol. 25, no 3.

Duggal K., Gupta L.R., Singh P. (2021) Gamification and Machine Learning Inspired Approach for Classroom Engagement and Learning. Mathematical Problems in Engineering, vol. 2021, Article ID 9922775.

Edwards B.I., Cheok A.D. (2018) Why Not Robot Teachers: Artificial Intelligence for Addressing Teacher Shortage. Applied Artificial Intelligence, vol. 32, no 4, pp. 345–360.

Ellis R.A., Goodyear P. (2010) Students' Experiences of e-Learning in Higher Education: The Ecology of Sustainable Innovation. New York NY: Routledge.

Fiallos A., Ochoa X. (2019) Semi-Automatic Generation of Intelligent Curricula to Facilitate Learning Analytics. Proceedings of the 9th International Conference on Learning Analytics & Knowledge (Tempe, Arizona, 2019, 04–08 March), pp. 46–50.

Fidan M., Gencel N. (2022) Supporting the Instructional Videos with Chatbot and Peer Feedback Mechanisms in Online Learning: The Effects on Learning Performance and Intrinsic Motivation. Journal of Educational Computing Research, vol. 60, no 6, Article no 073563312210779.

Fosch-Villaronga E., Lutz C., Tamò-Larrieux A. (2020) Gathering Expert Opinions for Social Robots’ Ethical, Legal, and Societal Concerns. International Journal of Social Robotics, vol. 12, no 2, pp. 441–458.

García E., Romero C., Ventura S., De Castro C. (2011) A Collaborative Educational Association Rule Mining Tool. The Internet and Higher Education, vol. 14, no 2, pp. 77–88.

Gardner J., O'Leary M., Yuan L. (2021) Artificial Intelligence in Educational Assessment: ‘Breakthrough? Or Buncombe and Ballyhoo? Journal of Computer Assisted Learning, vol. 37, no 5, pp. 1207–1216.

Garg S., Sharma S. (2020) Impact of Artificial Intelligence in Special Need Education to Promote Inclusive Pedagogy. International Journal of Information and Education Technology, vol. 10, no 7, pp. 523–527.

George G., Lal A.M. (2019) Review of Ontology-Based Recommender Systems in e-Learning. Computers & Education, vol. 142, December, Article no 103642.

Goksel N., Bozkurt A. (2019) Artificial Intelligence in Education: Current Insights and Future Perspectives. Handbook of Research on Learning in the Age of Transhumanism (eds S. Sisman-Ugur, G. Kurubacak), Hershey PA: IGI Global, pp. 224–236.

Guan C., Mou J., Jiang Z. (2020) Artificial Intelligence Innovation in Education: A Twenty-Year Data-Driven Historical Analysis. International Journal of Innovation Studies, vol. 4, no 4, pp. 134–147.

Guruge D.B., Kadel R., Halder S.J. (2021) The State of the Art in Methodologies of Course Recommender Systems — A Review of Recent Research. Data, no 6, Article no 18.

Hamam D. (2021) The New Teacher Assistant: A Review of Chatbots’ Use in Higher Education. Proceedings of the 23rd HCI International Conference, HCII 2021 (Virtual Event, 2021, 24–29 July), part III, pp. 59–63.

Harrathi M., Braham R. (2021) Recommenders in Improving Students’ Engagement in Large Scale Open Learning. Procedia Computer Science, vol. 192, no 1, pp. 1121–1131.

Hasanov A., Laine T.H., Chung T.-S. (2019) A Survey of Adaptive Context-Aware Learning Environments. Journal of Ambient Intelligence and Smart Environments, vol. 11, no 5, pp. 403–428.

Herodotou C., Rienties B., Boroowa A., Zdrahal Z., Hlosta M. (2019) A Large-Scale Implementation of Predictive Learning Analytics in Higher Education: The Teachers` Role and Perspective. Educational Technology Research and Development, vol. 67, no 2, pp. 1273–1306.

Herranz S.M., Palomo J., del Carmen de la Orden de la Cruz M. (2018) Building an Educational Platform Using NLP: A Case Study in Teaching Finance. Journal of Universal Computer Science, vol. 24, no 10, pp. 1403–1423.

Hooda M., Rana C., Dahiya O., Rizwan A., Hossain M.S. (2022) Artificial Intelligence for Assessment and Feedback to Enhance Student Success in Higher Education. Mathematical Problems in Engineering, vol. 2022, Article ID 5215722.

Jiang L. (2021) Virtual Reality Action Interactive Teaching Artificial Intelligence Education System. Complexity, vol. 2021, Article ID 5553211.

Jokhan A., Chand A.A., Singh V., Mamun K.A. (2022) Increased Digital Resource Consumption in Higher Educational Institutions and the Artificial Intelligence Role in Informing Decisions Related to Student Performance. Sustainability, no.14. pp. 4–13.

Joveliano D.A., Galli I.M., Dos Santos Júnior G.N., da Silva M.R.A., Benites C.D.S., Ribeiro F.C. (2020) Working with a Hearing Disability: A Proposal for Distance Teaching with Chabot. RISTI — Revista Iberica de Sistemas e Tecnologias de Informacao / Iberian Journal of Information Systems and Technologies, no E29, pp. 135–147.

Kabudi T., Pappas I., Olsen D.H. (2021) AI-Enabled Adaptive Learning Systems: A Systematic Mapping of the Literature. Computers & Education: Artificial Intelligence (CAEAI), vol. 2, Article no 100017.

Kizilkaya L., Vince D., Holmes W. (2019) Design Prompts for Virtual Reality in Education. Artificial Intelligence in Education. AIED 2019. Lecture Notes in Computer Science (eds S. Isotan, E. Millán, A. Ogan, P. Hastings, B. McLaren, R. Luckin), vol. 11626. Cham: Springe.

Kwon C. (2018) A Study on the Relationship of Distraction Factors, Presence, Flow, and Learning Effects in HMD-based Immersed VR Learning. Journal of Korea Multimedia Society, vol. 21, no 8, pp. 1002–1020.

Laal M., Ghodsi S.M. (2012) Benefits of Collaborative Learning. Procedia—Social and Behavioral Sciences, no 31, pp. 486–490.

Larrabee Sønderlund A., Hughes E., Smith J. (2019) The Efficacy of Learning Analytics Interventions in Higher Education: A Systematic Review. British Journal of Educational Technology, vol. 50, no 5, pp. 2594–2618.

Leaton Gray S. (2020) Artificial Intelligence in Schools: Towards a Democratic Future. London Review of Education, vol. 18, no 2, pp. 163–177.

Leeuwen van A., Janssen J., Erkens G., Brekelmans M. (2014) Supporting Teachers in Guiding Collaborating Students: Effects of Learning Analytics in CSCL. Computers & Education, vol. 79, October, pp. 28–39.

Leitner P., Khalil M., Ebner M. (2017) Learning Analytics in Higher Education—A Literature Review. Learning Analytics: Fundaments, Applications, and Trends (ed. A. Peña-Ayala), Cham, Switzerland: Springer, pp. 1–23.

Lim L.-A., Gentili S., Pardo A., Kovanović V., Whitelock-Wainwright A., Gašević D., Dawson S. (2021) What Changes, and for Whom? A Study of the Impact of Learning Analytics-Based Process Feedback in a Large Course. Learning and Instruction, vol. 72, Article no 101202.

Luckin R., Holmes W., Griffiths M., Forcier L.B. (2016) Intelligence Unleashed: An Argument for AI in Education. London: Pearson.

Lutz C., Schöttler M., Hofmann C. (2019) The Privacy Implications of Social Robots. Mobile Media & Communication, vol. 7, no 3, pp. 412–434.

Maitra S., Madan S., Kandwal R., Mahajan P. (2018) Mining Authentic Student Feedback for Faculty Using Naïve Bayes Classifier. Procedia—Computer Science, vol. 132, pp. 1171–1183.

Mangaroska K., Giannakos M. (2019) Learning Analytics for Learning Design: A Systematic Literature Review of Analytics-Driven Design to Enhance Learning. IEEE Transactions on Learning Technologies, vol. 12, no 4, pp. 516–534.

Martinho V.R.C., Nunes C., Minussi C.R. (2013) An Intelligent System for Prediction of School Dropout Risk Group in Higher Education Classroom Based on Artificial Neural Networks. Proceedings of the 25th IEEE International Conference on Tools with Artificial Intelligence. ICTAI 2013 (Herndon, VA, 2013, 04–06 November), pp. 159–166.

McCarthy J., Minsky M.L., Rochester N., Shannon C.E. (2006) A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence, August 31, 1955. AI Magazine, vol. 27, no 4, pp. 12–14.

Mihailescu M.I., Nita S.L., Pau V.C. (2016) New Big Data Model Based on Social Learning Environment Using Artificial Intelligence. E-learning Vision 2020! Conference Proceedings of ˮeLearning and Software for Educationˮ (eLSE), vol. 1, no 12, pp. 428–435.

Mirchi N., Bissonnette V., Yilmaz R., Ledwos N., Winkler-Schwartz A., Del Maestro R. (2020) The Virtual Operative Assistant: An Explainable Artificial Intelligence Tool for Simulation-Based Training in Surgery and Medicine. Plos One, vol. 15, no 2, Article no e0229596.

Mohamad S.K., Tasir Z. (2013) Educational Data Mining: A Review. Procedia—Social and Behavioral Sciences, vol. 97, pp. 320–324.

Montalvo S., Palomo J., de la Orden C. (2018) Building an Educational Platform Using NLP: A Case Study in Teaching Finance. Journal of Universal Computer Science, vol. 24, no 10, pp. 1403–1423.

Nkhoma C., Dang -Pham D., Hoang A.P., Nkhoma M., Le-Hoai T., Thomas S. (2019) Learning Analytics Techniques and Visualisation with Textual Data for Determining Causes of Academic Failure. Behaviour & Information Technology, vol. 39, no 9, pp. 808–823.

Nunn S., Avella J., Kanai T., Kebritchi M. (2016) Learning Analytics Methods, Benefits, and Challenges in Higher Education: A Systematic Literature Review. Online Learning Journal, vol. 20, no 2, pp. 1–17.

Ognjanovic I., Gasevic D., Dawson S. (2016) Using Institutional Data to Predict Student Course Selections in Higher Education. The Internet and Higher Education, vol. 29, no 2, pp. 49–62.

Ong V.K. (2016) Business Intelligence and Big Data Analytics for Higher Education: Cases from UK Higher Education Institutions. Information Engineering Express, vol. 2, no 1, pp. 65–75.

París-Requeiro M.T., Cabrero-Canosa M.J. (2010) Personalized Construction of Self-Evaluation Tests. 2010 IEEE Education Engineering Conference, EDUCON 2010 (Madrid, Spain, 2010, 14–16 April), pp. 863–868.

Pelletier K., McCormack M., Reeves J., Robert J., Arbino N., Grajek S. (2021) 2021 EDUCAUSE Horizon Report. Teaching and Learning Edition. Boulder, CO: EDUCAUSE.

Popenici S.A.D., Kerr S. (2017) Exploring the Impact of Artificial Intelligence on Teaching and Learning in Higher Education. Research and Practice in Technology Enhanced Learning, vol. 12, Article no 22.

Qureshi M.A., Khaskheli A., Qureshi J.A., Raza S.A., Yousufi S.Q. (2021) Factors Affecting Students’ Learning Performance through Collaborative Learning and Engagement. Interactive Learning Environments.

Raju A., Nair M., Nair A., Seenivasan R. (2018) Hybrid Learning Environment: Learning Mathematics Using ALEKS Software. International Conference on e-Learning P. 336–343.

Reiser R.A., Dempsey J.V. (eds) (2007) Trends and Issues in Instructional Design and Technology. Upper Saddle River NJ: Pearson.

Rienties B., Køhler Simonsen H., Herodotou C. (2020) Defining the Boundaries between Artificial Intelligence in Education, Computer-Supported Collaborative Learning, Educational Data Mining, and Learning Analytics: A Need for Coherence. Frontiers in Education, vol. 5, July, Article no 128.

Rincón-Flores E.G., Lopez-Camacho E., Mena J., Lopez O.O. (2020) Predicting Academic Performance with Artificial Intelligence (AI), a New Tool for Teachers and Students. Proceedings of the 11th IEEE Global Engineering Education Conference, EDUCON 2020 (Porto, Portugal, 2020, 27–30 April), pp. 1049–1054.

Romero C., Ventura S. (2010) Educational Data Mining: A Review of the State of the Art. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), vol. 40, no 6, pp. 601–618.

Romero C., Ventura S. (2007) Educational Data Mining: A Survey from 1995 to 2005. Expert Systems with Applications, vol. 33, no 1, pp. 135–146.

Ruan S., Jiang L., Xu Q., Liu Zh., Davis G. M., Brunskil E.l, Landay J. A. (2021) EnglishBot: An AI-Powered Conversational System for Second Language Learning. Proceedings of the 26th International Conference on Intelligent User Interfaces (IUI '21) (Virtually hosted by Texas A&M University, 2021, 13–17 April), pp. 434–444.

Seel N. M., Lehmann T., Blumschein P., Podolskiy O. A. (2017) Instructional Design for Learning: Theoretical Foundations. Rotterdam, NL: Sense.

Sergis S., Sampson D.G. (2017) Teaching and Learning Analytics to Support Teacher Inquiry: A Systematic Literature Review. Learning Analytics: Fundaments, Applications, and Trends. Studies in Systems, Decision and Control (ed. A. Peña-Ayala), Cham, Switzerland: Springer, pp. 25–63.

Shum S.B., Ferguson R. (2012) Social Learning Analytics. Journal of Educational Technology & Society, vol. 15, no 3, pp. 3–26.

Siemens G., Baker R.S.D. (2012) Learning Analytics and Educational Data Mining: Towards Communication and Collaboration. Proceedings of the 2nd international Conference on Learning Analytics and Knowledge (Vancouver, BC, 2012, 29 April — 2 May), pp. 252–254.

Siemens G., Long P. (2011) Penetrating the Fog: Analytics in Learning and Education. EDUCAUSE Review, vol. 46, no 5, P. 31–40.

Sohail S., Alvi A., Khanum A. (2022) Interpretable and Adaptable Early Warning Learning Analytics Model. CMC—Computers Materials & Continua, vol. 71, no 2, pp. 3211–3225.

Stoica A. S., Heras S., Palanca J., Julián V., Mihaescu M. C. (2021) Classification of Educational Videos by Using a Semi-Supervised Learning Method on Transcripts and Keywords. Neurocomputing, vol. 456, October, pp. 637–647.

Suganya G., Premalatha M., Dubey P., Drolia A.R., Srihari S.N. (2020) Subjective Areas of Improvement: A Personalized Recommendation. Procedia—Computer Science, vol. 172, pp. 235–239.

Syed T.A., Palade V., Iqbal R., Nair, S.S. (2017) A Personalized Learning Recommendation System Architecture for Learning Management System. Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (KDIR 2017) (Funchal, Madeira, Portugal, 2017, 01–03 November), pp. 275–282.

Tamayo P., Herrero A., Martín J.S., Navarro C., Tránchez, J.M. (2020) Design of a Chatbot as a Distance Learning Assistant. Open Praxis, vol. 12, no 1, pp. 145–153.

Thai-Nghe N., Drumond L., Krohn-Grimberghe A., Schmidt-Thieme L. (2010) Recommender System for Predicting Student Performance. Procedia—Computer Science, vol.1, pp. 2811–2819.

Tsai Y. S., Gasevic D. (2017) Learning Analytics in Higher Education—Challenges and Policies: A Review of Eight Learning Analytics Policies. Proceedings of the Seventh International Learning Analytics & Knowledge Conference (Vancouver, BC, 2017, 13–17 March), pp. 233–242.

Turhan M., Erol Y.C., Ekici, S. (2016) Predicting Students’ School Engagement Using Artificial Neural Networks. International Journal of Advances in Science, Engineering and Technology, vol. 4, iss. 2, pp. 159–62.

Variawa C., McCahan S. (2014) Engineering Vocabulary Development Using an Automated Software Tool. 121st ASEE Annual Conference (Indianapolis, IN, 2014, 15–18 June), Paper ID #8663.

Verbert K., Ochoa X., Derntl M., Wolpers M., Pardo A., Duval E. (2012) Semi-Automatic Assembly of Learning Resources. Computers & Education, vol. 59, no 4, pp. 1257–1272.

Yan H., Lin F. (2021) Including Learning Analytics in the Loop of Self-Paced Online Course Learning Design. International Journal of Artificial Intelligence in Education, vol. 31, no 4, pp. 878–895.

Zapata A., Domínguez V., Prieto M., Romero C. (2013) A Framework for Recommendation in Learning Object Repositories: An Example of Application in Civil Engineering. Advances in Engineering Software, vol. 56, February, pp. 1–14.

Zapata A., Menedoz V., Prieto M., Romero C. (2015) Evaluation and Selection of Group Recommendation Strategies for Collaborative Searching of Learning Objects. International Journal of Human-Computer Studies, vol. 76, April, pp. 22–39.

Zawacki-Richter O., Marin V. I., Bond M., Gouverneur F. (2019) Systematic Review of Research on Artificial Intelligence Applications in Higher Education—Where Are the Educators? International Journal of Educational Technology in Higher Education, vol. 16, no 1, pp. 27.

Zhang X., Cao Z. (2021) A Framework of an Intelligent Education System for Higher Education Based on Deep Learning. International Journal of Emerging Technologies in Learning vol. 16, no 7, pp. 233–248.

Zotou M., Tambouris E., Tarabanis K. (2020) Data-Driven Problem Based Learning: Enhancing Problem Based Learning with Learning Analytics. Educational Technology Research and Development, vol. 68, no 6, pp. 3393–3424.

How to Cite
Drugova, Elena, Irina Zhuravleva, Ulyana Zakharova, Valeriya Sotnikova, and Kristina Yakovleva. 2022. “Artificial Intelligence for Learning Analytics and Instructional Design Steps: An Overview of Solutions”. Voprosy Obrazovaniya / Educational Studies Moscow, no. 4 (December), 107-53.
Research Articles