Skip to main content
SpringerLink
Log in

Teaching and Learning Analytics to Support Teacher Inquiry: A Systematic Literature Review

  • Chapter
  • First Online:
Learning Analytics: Fundaments, Applications, and Trends

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 94))

Abstract

Teacher inquiry is identified as a key global need for driving the continuous improvement of the teaching and learning conditions for learners. However, specific barriers (mainly related to teachers’ data literacy competences), can defer teachers from engaging with inquiry to improve their teaching practice. To alleviate these barriers and support teacher inquiry, the concept of Teaching and Learning Analytics (TLA) has been proposed, as a complementing synergy between Teaching Analytics and Learning Analytics. Teaching and Learning Analytics aims to provide a framework in which the insights generated by Learning Analytics methods and tools can become meaningfully translated for driving teachers’ inquiry to improve their teaching practice, captured through Teaching Analytics methods and tools. In this context, TLA have been identified as a research challenge with significant practical impact potential. This chapter contributes the first systematic literature review in the emerging research field of Teaching and Learning Analytics. The insights gained from the systematic literature review aim to (a) transparently outline the existing state-of-the-art following a structured analysis methodology, as well as (b) elicit insights and shortcomings which could inform future work in the Teaching and Learning Analytics research field.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 129.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 179.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    In this book chapter, we will consider this extended strand of Teaching Analytics research as part of the proposed concept of Teaching and Learning Analytics (TLA) and not as part of the Teaching Analytics strand.

Abbreviations

ED:

Educational design

RQ:

Research question

SLR:

Systematic literature review

SNA:

Social network analysis

TLA:

Teaching and learning analytics

References

  • Agudo-Peregrina ÁF, Iglesias-Pradas S, Conde-González MÁ et al (2014) Can we predict success from log data in VLEs? Classification of interactions for learning analytics and their relation with performance in VLE-supported F2F and online learning. Comput Hum Behav 31:542–550

    Article  Google Scholar 

  • Ali L, Hatala M, Gašević D et al (2012) A qualitative evaluation of evolution of a learning analytics tool. Comput Educ 58(1):470–489

    Article  Google Scholar 

  • Altrichter H, Feldman A, Posch P et al (2008) Teachers investigate their work: an introduction to action research across the professions. Routledge, London

    Google Scholar 

  • Avramides K, Hunter J, Oliver M et al (2015) A method for teacher inquiry in cross-curricular projects: lessons from a case study. Br J Educ Technol 46(2):249–264

    Article  Google Scholar 

  • Bakharia A, Corrin L, de Barba P et al (2016) A conceptual framework linking learning design with learning analytics. Paper presented at the 6th international conference on learning analytics & knowledge, Edinburgh, 25–29 April 2016

    Google Scholar 

  • Bos N, Brand-Gruwel S (2016) Student differences in regulation strategies and their use of learning resources: implications for educational design. Paper presented at the 6th international conference on learning analytics & knowledge, Edinburgh, 25–29 April 2016

    Google Scholar 

  • Brereton P, Kitchenham BA, Budgen D et al (2007) Lessons from applying the systematic literature review process within the software engineering domain. J Syst Softw 80(4):571–583

    Article  Google Scholar 

  • Camilleri V, de Freitas S, Montebello M et al (2013) A case study inside virtual worlds: use of analytics for immersive spaces. Paper presented at the 3rd international conference on learning analytics and knowledge, Leuven, 8–12 April 2013

    Google Scholar 

  • Check J, Schutt R (2012) Research methods in education. Sage Publications, London

    Google Scholar 

  • Chounta IA, Avouris N (2016). Towards the real-time evaluation of collaborative activities: integration of an automatic rater of collaboration quality in the classroom from the teacher’s perspective. Education and Information Technologies, 1–21

    Google Scholar 

  • Dana NF, Yendol-Hoppey D (2014) The reflective educator’s guide to classroom research: learning to teach and teaching to learn through practitioner inquiry. Corwin Press, London

    Google Scholar 

  • Dawson S (2010) ‘Seeing’the learning community: an exploration of the development of a resource for monitoring online student networking. Br J Educ Technol 41(5):736–752

    Article  Google Scholar 

  • Dawson SP, McWilliam E, Tan JPL (2008) Teaching smarter: how mining ICT data can inform and improve learning and teaching practice. Paper presented at the 2008 ASCILITE conference, Melbourne, 20 Nov–3 Dec 2008

    Google Scholar 

  • Dunbar RL, Dingel MJ, Prat-Resina X (2014) Connecting analytics and curriculum design: process and outcomes of building a tool to browse data relevant to course designers. J Learn Analytics 1(3):220–240

    Article  Google Scholar 

  • Duque R, Gómez-Pérez D, Nieto-Reyes A et al (2015) Analyzing collaboration and interaction in learning environments to form learner groups. Comput Hum Behav 47:42–49

    Article  Google Scholar 

  • Dyckhoff AL (2011) Implications for learning analytics tools: a meta-analysis of applied research questions. Int J Comput Inf Syst Ind Manage Appl 3:594–601

    Google Scholar 

  • Dyckhoff AL, Zielke D, Bültmann M et al (2012) Design and implementation of a learning analytics toolkit for teachers. Educ Technol Soc 15(3):58–76

    Google Scholar 

  • Dyckhoff AL, Lukarov V, Muslim A et al (2013) Supporting action research with learning analytics. Paper presented at the 3rd international conference on learning analytics and knowledge, Leuven, 8–12 April 2013

    Google Scholar 

  • Elbadrawy A, Studham S, Karypis G (2014) Personalized multi-regression models for predicting students performance in course activities. Paper presented at the 5th international conference on learning analytics and knowledge, NY, 16–20 March 2015

    Google Scholar 

  • El-Bishouty MM, Saito K, Chang T et al (2015) Teaching improvement technologies for adaptive and personalized learning environments. In: Kinshuk, Huang R (eds) Ubiquitous learning environments and technologies, Springer, Berlin, pp 225–242

    Google Scholar 

  • Emin-Martinez V, Hansen C, Rodrıguez Triana MJ et al (2014) Towards teacher-led design inquiry of learning. eLearning Papers (36)

    Google Scholar 

  • Fernández-Delgado M, Mucientes M, Vazquez-Barreiros B et al (2014) Learning analytics for the prediction of the educational objectives achievement. Paper presented at the Frontiers in Education Conference, Madrid, 22–25 Oct 2014

    Google Scholar 

  • Fernández-Gallego B, Lama M, Vidal JC et al (2013) Learning analytics framework for educational virtual worlds. Procedia Comput Sci 25:443–447

    Article  Google Scholar 

  • Fritz J (2016) LMS course design as learning analytics variable. Paper presented at the 6th international conference on learning analytics & knowledge, 1st learning analytics for curriculum and program quality improvement workshop, Edinburgh, 25–29 April 2016

    Google Scholar 

  • Fulantelli G, Taibi D, Arrigo M (2015) A framework to support educational decision making in mobile learning. Comput Hum Behav 47:50–59

    Article  Google Scholar 

  • Gauthier G (2013) Using teaching analytics to inform assessment practices in technology mediated problem solving tasks. In IWTA@ LAK

    Google Scholar 

  • Gómez-Aguilar DA, Hernández-García Á, García-Peñalvo FJ et al (2015) Tap into visual analysis of customization of grouping of activities in eLearning. Comput Hum Behav 47:60–67

    Article  Google Scholar 

  • Govaerts S, Verbert K, Duval E (2011) Evaluating the student activity meter: two case studies. In: Leung H, Popescu E, Cao Y et al (eds) Advances in web-based learning-ICWL 2011. Springer, Berlin, pp 188–197

    Chapter  Google Scholar 

  • Greller W, Drachsler H (2012) Translating learning into numbers: a generic framework for learning analytics. Educ Technol Soc 15(3):42–57

    Google Scholar 

  • Greller W, Ebner M, Schön M (2014) Learning analytics: from theory to practice—data support for learning and teaching. In: Kalz M, Marco R (eds) Computer assisted assessment. Research into e-assessment, Springer International Publishing, pp 79–87

    Google Scholar 

  • Hansen CJ, Wasson B (2016) Teacher inquiry into student learning: the TISL heart model and method for use in teachers’ professional development. Nordic J Digital Literacy 10(1):24–49

    Article  Google Scholar 

  • Haya PA, Daems O, Malzahn N et al (2015) Analysing content and patterns of interaction for improving the learning design of networked learning environments. Br J Educ Technol 46(2):300–316

    Article  Google Scholar 

  • Hernández-García Á, González-González I, Jiménez-Zarco AI et al (2015) Applying social learning analytics to message boards in online distance learning: a case study. Comput Hum Behav 47:68–80

    Article  Google Scholar 

  • Howlin C, Lynch D (2014) Learning and academic analytics in the Realizeit System. Paper presented at the world conference on e-learning in corporate, government, healthcare, and higher education, Louisiana, 2014

    Google Scholar 

  • Hung JL, Hsu YC, Rice K (2012) Integrating data mining in program evaluation of K-12 online education. Educ Technol Soc 15(3):27–41

    Google Scholar 

  • Jaggars SS, Xu D (2016) How do online course design features influence student performance? Comput Educ 95:270–284

    Article  Google Scholar 

  • Karkalas S, Mavrikis M (2016) Towards analytics for educational interactive e-books: the case of the reflective designer analytics platform (RDAP). Paper presented at the 6th international conference on learning analytics & knowledge, Edinburgh, 25–29 April 2016

    Google Scholar 

  • Kaufman TE, Graham CR, Picciano AG et al (2014) Data-driven decision making in the K-12 classroom. In: Spector JM, Merrill MD, Elen J, Bishop MJ (eds) Handbook of research on educational communications and technology. Springer, New York, pp 337–346

    Chapter  Google Scholar 

  • Kitchenham B, Charters S (2007) Guidelines for performing systematic literature reviews in software engineering. Keele University and Durham University

    Google Scholar 

  • Kladich S, Ives C, Parker N et al (2013) Extending the AAT tool with a user-friendly and powerful mechanism to retrieve complex information from educational log data. In: Human-computer interaction and knowledge discovery in complex, unstructured, big data. Springer, Berlin, pp 334–341

    Google Scholar 

  • Kosba E, Dimitrova V, Boyle R (2005) Using student and group models to support teachers in web-based distance education. User modeling 2005. Springer, Berlin, pp 124–133

    Chapter  Google Scholar 

  • Lockyer L, Heathcote E, Dawson S (2013) Informing pedagogical action: aligning learning analytics with learning design. Am Behav Sci 57(10):1439–1459

    Article  Google Scholar 

  • Mandinach E (2012) A perfect time for data use: using data driven decision making to inform practice. Educ Psychol 47(2):71–85

    Article  Google Scholar 

  • Marcos-García JA, Martínez-Monés A, Dimitriadis Y (2015) DESPRO: a method based on roles to provide collaboration analysis support adapted to the participants in CSCL situations. Comput Educ 82:335–353

    Article  Google Scholar 

  • Marsh JA, Farrell CC (2014) How leaders can support teachers with data-driven decision making a framework for understanding capacity building. Educ Manage Adm Leadersh 1–21

    Google Scholar 

  • Martinez-Maldonado R, Schneider B, Charleer S et al (2016) Interactive surfaces and learning analytics: data, orchestration aspects, pedagogical uses and challenges. Paper presented at the 6th international conference on learning analytics & knowledge, Edinburgh, 25–29 April 2016

    Google Scholar 

  • Mazza R, Dimitrova V (2007) CourseVis: a graphical student monitoring tool for supporting instructors in web-based distance courses. Int J Hum Comput Stud 65(2):125–139

    Article  Google Scholar 

  • Mazza R, Bettoni M, Faré M et al (2012) Moclog–monitoring online courses with log data. Paper presented at the 1st moodle research conference, Heraklion, Crete, 14–15 Sept 2012

    Google Scholar 

  • Mazza R, Milani C (2005) Exploring usage analysis in learning systems: gaining insights from visualisations. Paper presented at the communication dans: the workshop on usage analysis in learning systems, the twelfth international conference on artificial intelligence in education, pp 65–72

    Google Scholar 

  • McKenney S, Mor Y (2015) Supporting teachers in data-informed educational design. Br J Educ Technol 46(2):265–279

    Article  Google Scholar 

  • Melero J, Hernandez-Leo D, Sun J et al (2015) How was the activity? A visualization support for a case of location-based learning design. Br J Educ Technol 46(2):317–329

    Article  Google Scholar 

  • Mendez G, Ochoa X, Chiluiza K et al (2014) Curricular design analysis: a data-driven perspective. J Learn Analytics 1(3):84–119

    Article  Google Scholar 

  • Merceron A (2012) Investigating the core group effect in usage of resources with analytics. Paper presented at the 2nd international conference on learning analytics and knowledge, Vancouver, 29 April–02 May 2012

    Google Scholar 

  • Minović M, Milovanović M, Šošević U et al (2015) Visualisation of student learning model in serious games. Comput Hum Behav 47:98–107

    Article  Google Scholar 

  • Mirriahi N, Dawson S (2013) The pairing of lecture recording data with assessment scores: a method of discovering pedagogical impact. Paper presented at the 3rd international conference on learning analytics and knowledge, Leuven, 8–12 April 2013

    Google Scholar 

  • Monroy C, Rangel VS, Bell ER et al (2015) A learning analytics approach to characterize and analyze inquiry-based pedagogical processes. Paper presented at the 5th international conference on learning analytics and knowledge, NY, 16–20 March 2015

    Google Scholar 

  • Mor Y, Ferguson R, Wasson B (2015) Editorial: learning design, teacher inquiry into student learning and learning analytics: a call for action. Br J Educ Technol 46(2):221–229

    Article  Google Scholar 

  • Nunn S, Avella JT, Kanai T et al (2016) Learning analytics methods, benefits, and challenges in higher education: a systematic literature review. Online Learning 20(2)

    Google Scholar 

  • Ochoa X (2016) Simple metrics for curricular analytics. Paper presented at the 6th international conference on learning analytics & knowledge, 1st learning analytics for curriculum and program quality improvement workshop Edinburgh, 25–29 April 2016

    Google Scholar 

  • OECD (2009) Teacher evaluation: a conceptual framework and examples of country practices. OECD review on evaluation and assessment frameworks for improving school outcomes. http://www.oecd.org/edu/school/44568106.pdf. Accessed 22 Aug 2016

  • OECD (2013) Teachers for the 21st century: using evaluation to improve teaching. OECD Publishing. http://www.oecd.org/site/eduistp13/TS2013%20Background%20Report.pdf. Accessed 22 Aug 2016

  • Papamitsiou Z, Economides A (2014) Learning analytics and educational data mining in practice: a systematic literature review of empirical evidence. Educ Technol Soc 17(4):49–64

    Google Scholar 

  • Pardo A, Ellis RA, Calvo RA (2015) Combining observational and experiential data to inform the redesign of learning activities. Paper presented at the 5th international conference on learning analytics and knowledge, NY, 16–20 March 2015

    Google Scholar 

  • Prieto LP, Villagrá-Sobrino S, Jorrín-Abellán IM et al (2011) Recurrent routines: analyzing and supporting orchestration in technology-enhanced primary classrooms. Comput Educ 57(1):1214–1227

    Article  Google Scholar 

  • Prieto LP, Sharma K, Dillenbourg P et al (2016) Teaching analytics: towards automatic extraction of orchestration graphs using wearable sensors. Paper presented at the 6th international conference on learning analytics & knowledge, Edinburgh, 25–29 April 2016

    Google Scholar 

  • Rienties B, Toetenel L, Bryan A (2015) “Scaling up” learning design: impact of learning design activities on LMS behavior and performance. Paper presented at the 5th international conference on learning analytics and knowledge, NY, 16–20 March 2015

    Google Scholar 

  • Rodríguez-Triana MJ, Martínez-Monés A, Asensio-Pérez JI et al (2015) Scripting and monitoring meet each other: aligning learning analytics and learning design to support teachers in orchestrating CSCL situations. Br J Educ Technol 46(2):330–343

    Article  Google Scholar 

  • Romero C, Ventura S, García E (2008) Data mining in course management systems: Moodle case study and tutorial. Comput Educ 51(1):368–384

    Article  Google Scholar 

  • Sin K, Muthu L (2015) Application of big data in education data mining and learning analytics—a literature review. J Soft Comput 5(4):1035–1049

    Article  Google Scholar 

  • Slotta JD, Tissenbaum M, Lui M (2013) Orchestrating of complex inquiry: three roles for learning analytics in a smart classroom infrastructure. Paper presented at the 3rd international conference on learning analytics and knowledge, Leuven, 8–12 April 2013

    Google Scholar 

  • Smolin D, Butakov S (2012) Applying artificial intelligence to the educational data: an example of syllabus quality analysis. Paper presented at the 2nd international conference on learning analytics and knowledge, Vancouver, 29 April–02 May 2012

    Google Scholar 

  • Society for Learning Analytics Research (SOLAR) (2011) Proceedings of the 1st international conference on learning analytics and knowledge

    Google Scholar 

  • Schwarz BB, Asterhan CS (2011) E-moderation of synchronous discussions in educational settings: a nascent practice. J Learn Sci 20(3):395–442

    Article  Google Scholar 

  • Timperley H, Wilson A, Barrar H et al (2010) Teacher professional learning and development. Report for the New Zealand Ministry of Education. http://www.oecd.org/edu/school/48727127.pdf Accessed 22 Aug 2016

  • Toetenel L, Rienties B (2016) Analysing 157 learning designs using learning analytic approaches as a means to evaluate the impact of pedagogical decision making. Br J Educ Technol 47(5):981–992

    Article  Google Scholar 

  • Van Leeuwen A, Janssen J, Erkens G et al (2014) Supporting teachers in guiding collaborating students: effects of learning analytics in CSCL. Comput Educ 79:28–39

    Article  Google Scholar 

  • van Leeuwen A, Janssen J, Erkens G et al (2015) Teacher regulation of cognitive activities during student collaboration: effects of learning analytics. Comput Educ 90:80–94

    Article  Google Scholar 

  • Wasson B, Hanson C, Mor Y (2016) Grand challenge problem 11: empowering teachers with student data. In: Eberle J, Lund K, Tchounikine P, Fischer F (eds) Grand challenge problems in technology-enhanced learning II: MOOCs and beyond. International Publishing, Springer, New York, pp 55–58

    Chapter  Google Scholar 

  • Wong WY, Lavrencic M (2016) Using a risk management approach in analytics for curriculum and program quality improvement. In Paper presented at the 6th international conference on learning analytics & knowledge, 1st learning analytics for curriculum and program quality improvement workshop Edinburgh, 25–29 April 2016

    Google Scholar 

  • Yen CH, Chen IC, Lai SC et al (2015) An analytics-based approach to managing cognitive load by using log data of learning management systems and footprints of social media. Educ Technol Soc 18(4):141–158

    Google Scholar 

  • Zhang H, Almeroth K, Knight A et al (2007) Moodog: tracking students’ online learning activities. Paper presented at the world conference on educational multimedia, hypermedia and telecommunications, Vancouver, 25–29 June 2007

    Google Scholar 

Download references

Acknowledgements

The work presented in this paper has been partially funded by National Matching Funds 2014–2016 of the Greek Government, and more specifically by the General Secretariat for Research and Technology (GSRT), related to EU project “Inspiring Science: Large Scale Experimentation Scenarios to Mainstream eLearning in Science, Mathematics and Technology in Primary and Secondary Schools” (GA No. 325123).

Author information

Authors and Affiliations

  1. Department of Digital Systems, University of Piraeus, Androutsou 150, 18532, Piraeus, Greece

    Stylianos Sergis & Demetrios G. Sampson

  2. School of Education, Curtin University, Building 501 Level 4, Bentley Campus, Kent Street, Bentley, Perth, WA, 6102, Australia

    Demetrios G. Sampson

Authors
  1. Stylianos Sergis
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Demetrios G. Sampson
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Demetrios G. Sampson .

Editor information

Editors and Affiliations

  1. Instituto Politécnico Nacional, WOLNM & Escuela Superior de Ingeniería,Mecánica y Eléctrica, Zacatenco, México DF, Mexico

    Alejandro Peña-Ayala

Appendix

Appendix

Table 2.9 depicts the full analysis of the 54 identified TLA research works, in terms of the Research Questions of the systematic literature review.

Table 2.9 Analysis of research works included in the SLR
Full size table

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this chapter

Cite this chapter

Sergis, S., Sampson, D.G. (2017). Teaching and Learning Analytics to Support Teacher Inquiry: A Systematic Literature Review. In: Peña-Ayala, A. (eds) Learning Analytics: Fundaments, Applications, and Trends. Studies in Systems, Decision and Control, vol 94. Springer, Cham. https://doi.org/10.1007/978-3-319-52977-6_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-52977-6_2

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-52976-9

  • Online ISBN: 978-3-319-52977-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation