November 13, 2025

Radios Tech

Connecting the World with Radio Technology

Relations between teachers’ technology integration within ICAP modes with moderation effects: international perspective

Relations between teachers’ technology integration within ICAP modes with moderation effects: international perspective
  • Adebayo KA, Ntokozo N, Grace NZ (2020) Availability of educational resources and student academic performances in South Africa. Univers J Educ Res 8(8):3768–3781

    Article 

    Google Scholar 

  • Anđić B, Maričić M, Weinhandl R, Mumcu F, Schmidthaler E, Lavicza Z (2024) Metaphorical evolution: A longitudinal study of secondary school teachers’ concepts of 3D modelling and printing in education. Educ Inf Technol 29(11):14091–14126. https://doi.org/10.1007/s10956-022-10005-0

    Article 

    Google Scholar 

  • Anđić B, Ulbrich E, Dana-Picard T, Cvjetićanin S, Petrović F, Lavicza Z, Maričić M (2023) A phenomenography study of STEM teachers’ conceptions of using three-dimensional modeling and printing (3DMP) in teaching. J Sci Educ Technol 32(1):45–60

    Article 

    Google Scholar 

  • Antonietti C, Schmitz ML, Consoli T, Cattaneo A, Gonon P, Petko D (2023) Development and validation of the ICAP Technology Scale to measure how teachers integrate technology into learning activities. Comput Educ 192:104648

    Article 

    Google Scholar 

  • Ayanwale MA, Adelana OP, Odufuwa TT (2024) Exploring STEAM teachers’ trust in AI-based educational technologies: A structural equation modelling approach. Discov Educ 3:1–22

    Article 

    Google Scholar 

  • Berman JJ (2016) Data simplification. Elsevier. https://doi.org/10.1016/C2015-0-00783-3

  • Bosch C, Laubscher DJ (2019) Cooperative learning as a strategy for self-directed learning in blended-distance learning environments: A systematic literature review. Student support toward self-directed learning in open and distributed environments 1–25

  • Branko A, Šorgo A, Helm C, Weinhandl R, Lang V (2023) Exploring factors affecting elementary school teachers’ adoption of 3D printers in teaching. TechTrends 67(6):990–1006. https://doi.org/10.1007/s11528-023-00909-y

    Article 

    Google Scholar 

  • Buhari B, Sari RM (2022) Development of laboratory skills application based on android as a media of flipped learning model for nursing student. Malays J Nurs 14:30–35

    Article 

    Google Scholar 

  • Byrne BM (2013) Structural equation modeling with Mplus: Basic concepts, applications, and programming (1st ed.). Routledge. https://doi.org/10.4324/9780203807644

  • Byrne BM (2016) Structural equation modeling with AMOS. Routledge. https://doi.org/10.4324/9781315757421

  • Cai Z, Fan X, Du J (2017) Gender and attitudes toward technology use: A meta-analysis. Comput Educ 105:1–13

    Article 

    Google Scholar 

  • Cheung AC, Slavin RE (2011) The effectiveness of education technology for enhancing reading achievement: a meta-analysis. Center for Research and Reform in Education

  • Chi MT (2009) Active-constructive-interactive: a conceptual framework for differentiating learning activities. Top Cogn Sci 1:73–105

    Article 
    PubMed 

    Google Scholar 

  • Chi MT, Boucher NS (2023) Applying the ICAP framework to improve classroom learning. In: In their own words: What scholars want you to know about why and how to apply the science of learning in your academic setting. American Psychological Association, pp 94–110

  • Chi MT, Adams J, Bogusch EB, Bruchok C, Kang S, Lancaster M, Yaghmourian DL (2018) Translating the ICAP theory of cognitive engagement into practice. Cogn Sci 42:1777–1832

    Article 

    Google Scholar 

  • Chi MT, Wylie R (2014) The ICAP framework: linking cognitive engagement to active learning outcomes. Educ Psychol 49:219–243

    Article 

    Google Scholar 

  • Chi MTH, Roy M, Hausmann RGM (2008) Observing tutoring collaboratively: Insights about tutoring effectiveness from vicarious learning. Cogn Sci 32:301–341

    Article 
    PubMed 

    Google Scholar 

  • Chien YT, Chang YH, Chang CY (2016) Do we click in the right way? A meta-analytic review of clicker-integrated instruction. Educ Res Rev 17:1–18

    Article 

    Google Scholar 

  • Cohen L, Manion L, Morrison K (2002) Research methods in education. Routledge

  • Consoli T, Désiron J, Cattaneo A (2023) What is “technology integration” and how is it measured in K-12 education? A systematic review of survey instruments from 2010 to 2021. Comput Educ 10:42–47

    Google Scholar 

  • Coppe T, Parmentier M, Kelchtermans G, Raemdonck I, März V, Colognesi S (2024) Beyond traditional narratives about teacher professional development: A critical perspective on teachers’ working life. Teach Teach Educ 139:104436

    Article 

    Google Scholar 

  • Cussó-Calabuig R, Farran XC, Bosch-Capblanch X (2018) Effects of intensive use of computers in secondary school on gender differences in attitudes towards ICT: A systematic review. Educ Inf Technol 23:2111–2139

    Article 

    Google Scholar 

  • Dunn TJ, Baguley T, Brunsden V (2014) From alpha to omega: A practical solution to the pervasive problem of internal consistency estimation. Br J Psychol 105:399–412. https://doi.org/10.1111/bjop.12046

    Article 
    PubMed 

    Google Scholar 

  • Eros J (2011) The career cycle and the second stage of teaching: Implications for policy and professional development. Arts Educ Policy Rev 112:65–70

    Article 

    Google Scholar 

  • Fütterer T, Hoch E, Lachner A, Scheiter K, Stürmer K (2023) High-quality digital distance teaching during COVID-19 school closures: Does familiarity with technology matter? Comput Educ 199:47–68

    Article 

    Google Scholar 

  • Fütterer T, Scheiter K, Cheng X, Stürmer K (2022) Quality beats frequency? Investigating students’ effort in learning when introducing technology in classrooms. Contemp Educ Psychol 69:102042

    Article 

    Google Scholar 

  • Giacomo DD, Ranieri J, Lacasa P (2017) Digital learning as enhanced learning processing? Cognitive evidence for new insight of smart learning. Front Psychol 8:13–29

    Article 

    Google Scholar 

  • Gobert JD, Baker RS, Wixon MB (2015) Operationalizing and detecting disengagement within online science microworlds. Educ Psychol 50:43–57

    Article 

    Google Scholar 

  • Grimley M (2012) Digital leisure-time activities, cognition, learning behaviour and information literacy: what are our children learning? E-Learn Digit Media 9:13–28

    Article 

    Google Scholar 

  • Gui Y, Cai Z, Yang Y, Kong L, Fan X, Tai RH (2023) Effectiveness of digital educational game and game design in STEM learning: A meta-analytic review. Int J STEM Educ 10:1

    Article 

    Google Scholar 

  • Hair JF, Black WC, Babin BJ, Anderson RE (2010) Multivariate data analysis: A global perspective. 7th edn. Upper Saddle River, NJ: Prentice Hall

  • Hillmayr D, Ziernwald L, Reinhold F, Hofer SI, Reiss KM (2020) The potential of digital tools to enhance mathematics and science learning in secondary schools: A context-specific meta-analysis. Comput Educ 153:103897

    Article 

    Google Scholar 

  • International Telecommunication Union (2023) Measuring digital development: Facts and figures 2023. https://www.itu.int/itu-d/reports/statistics/facts-figures-2023/

  • International Telecommunication Union (2024) Measuring digital development: Facts and figures 2024. A (2006) The impact of institutional size on student engagement. NASPA J 43:87–114

  • Kock N (2014) Advanced mediating effects tests, multi-group analyses, and measurement model assessments in PLS-based SEM. Int J E-Collab 10:1–13

    Google Scholar 

  • Kümmel E et al. (2020) Digital learning environments in higher education: a literature review of the role of individual vs. social settings for measuring learning outcomes. Educ Sci 10:78

    Article 

    Google Scholar 

  • Ma W, Adesope OO, Nesbit JC, Liu Q (2014) Intelligent tutoring systems and learning outcomes: a meta-analysis. J Educ Psychol 106:901–901

    Article 

    Google Scholar 

  • Maričić, M., Anđić, B., Mumcu, F., Rokos, L., Vondruška, J., Weinhandl, R., … & Špernjak, A. (2024) Evaluating the quality of technology integration across seven European countries with the ICAP Technology Scale. Journal of Computers in Education, 1-38. https://doi.org/10.1007/s40692-024-00341-y

  • Maričić M, Anđić B, Soeharto S, Mumcu F, Cvjetićanin S, Lavicza Z (2025) The exploration of continuous teaching intention in emerging-technology environments through perceived cognitive load, usability, and teacher’s attitudes. Educ Inf Technol 30(7):9341–9370. https://doi.org/10.1007/s10639-024-13141-9

    Article 

    Google Scholar 

  • Maričić M, Cvjetićanin S, Anđić B, Marić M, Petojević A (2023) Using instructive simulations to teach young students simple science concepts: Evidence from electricity content. J Res Technol Educ 56(6):691–710. https://doi.org/10.1080/15391523.2023.2196460

    Article 

    Google Scholar 

  • Muthén B, Muthén L (2018) Mplus user’s guide and diagrammer documentation. The Comprehensive Modelling Program for Applied Researchers: User’s Guide, 5

  • Ninković S, Florić OK, Momčilović M (2023) Multilevel analysis of the effects of principal support and innovative school climate on the integration of technology in learning activities. Comput Educ 202:104833

    Article 

    Google Scholar 

  • Oliveira A, Feyzi Behnagh R, Ni L, Mohsinah AA, Burgess KJ, Guo L (2019) Emerging technologies as pedagogical tools for teaching and learning science: a literature review. Hum Behav Emerg Technol 1:149–16

    Article 

    Google Scholar 

  • Praetorius AK, Klieme E, Herbert B, Pinger P (2018) Generic dimensions of teaching quality: The German framework of three basic dimensions. ZDM Math Educ 50:407–426

    Article 

    Google Scholar 

  • Perera M, Aboal D (2019) The impact of a mathematics computer-assisted learning platform on students’ mathematics test scores. Maastricht Economic and Social Research Institute on Innovation and Technology (UNU-MERIT). https://www.merit.unu.edu/publications/wppdf/2019/wp2019-007.pdf

  • Ran H, Kim NJ, Secada WG (2022) A meta‐analysis on the effects of technology’s functions and roles on students’ mathematics achievement in K‐12 classrooms. J Comput Assist Learn 38:258–284

    Article 

    Google Scholar 

  • Ritter LN (2017) Technology acceptance model of online learning management systems in higher education: a meta-analytic structural equation mode. l Int J Learn Manag Syst 5:1–16

    Article 

    Google Scholar 

  • Sailer M, Stadler M, Schultz-Pernice F, Franke U, Schöffmann C, Paniotova V, Fischer F (2021) Technology-related teaching skills and attitudes: validation of a scenario-based self-assessment instrument for teachers. Comput Hum Behav 115:106635

    Article 

    Google Scholar 

  • Schauble L, Glaser R, Duschl RA, Schulze S, John J (2009) Students’ understanding of the objectives and procedures of experimentation in the science classroom. J Learn Sci 4:131–166

    Article 

    Google Scholar 

  • Scherer R, Siddiq F, Tondeur J (2019) The technology acceptance model (TAM): a meta-analytic structural equation modeling approach to explaining teachers’ adoption of digital technology in education. Comput Educ 128:13–35

    Article 

    Google Scholar 

  • Scherer R, Teo T (2019) Unpacking teachers’ intentions to integrate technology: a meta-analysis. Educ Res Rev 27:90–109

    Article 

    Google Scholar 

  • Schmitz ML, Antonietti C, Consoli T, Cattaneo A, Gonon P, Petko D (2023) Transformational leadership for technology integration in schools: Empowering teachers to use technology in a more demanding way. Comput Educ 204:1–15. https://doi.org/10.1016/j.compedu.2023.104880

    Article 

    Google Scholar 

  • Schwartz DL, Chase CC, Oppezzo MA, Chin DB (2011) Practicing versus inventing with contrasting cases: the effects of telling first on learning and transfer. J Educ Psychol 103:759–775

    Article 

    Google Scholar 

  • Stegmann K (2020) Effekte digitalen Lernens auf den Wissens- und Kompetenzenerwerb in der Schule: eine Integration metaanalytischer Befunde [Effects of digital learning for knowledge acquisition and competence development in school: an integration of meta-analytic evidence]. Z Padagogik 66:174–190

    Google Scholar 

  • Sung YT, Chang KE, Liu TC (2016) The effects of integrating mobile devices with teaching and learning on students’ learning performance: a meta-analysis and research synthesis. Comput Educ 94:252–275

    Article 

    Google Scholar 

  • Taber KS (2018) The use of Cronbach’s alpha when developing and reporting research instruments in science education. Res Sci Educ 48:1273–1296. https://doi.org/10.1007/s11165-016-9602-2

    Article 

    Google Scholar 

  • Teng Z, Cai Y, Gao Y, Zhang X, Li X (2022) Factors affecting learners’ adoption of an educational metaverse platform: An empirical study based on an extended UTAUT model. Mob Inf Syst 2022(1):5479215

    Google Scholar 

  • Torenbeek M, Peters V (2017) Explaining attrition and decreased effectiveness of experienced teachers: A research synthesis. Work 57:397–407. https://doi.org/10.3233/wor-172575

    Article 
    PubMed 

    Google Scholar 

  • Timotheou S, Miliou O, Dimitriadis Y, Sobrino SV, Giannoutsou N, Cachia R, Ioannou A (2023) Impacts of digital technologies on education and factors influencing schools’ digital capacity and transformation: a literature review. Educ Inf Technol 28:6695–6726

    Article 

    Google Scholar 

  • Tolba EG, Youssef NH (2022) High school science teachers’ acceptance of using distance education in the light of UTAUT. Eurasia J Math Sci Technol Educ 18

  • Vogel F, Wecker C, Kollar I, Fischer F (2017) Socio-cognitive scaffolding with computer-supported collaboration scripts: a meta-analysis. Educ Psychol Rev 29:477–511

    Article 

    Google Scholar 

  • Wang J, Tigelaar DE, Zhou T, Admiraal W (2023) The effects of mobile technology usage on cognitive, affective, and behavioural learning outcomes in primary and secondary education: a systematic review with meta‐analysis. J Comput Assist Learn 39:301–328

    Article 

    Google Scholar 

  • Wekerle C, Daumiller M, Kollar I (2022) Using digital technology to promote higher education learning: the importance of different learning activities and their relations to learning outcomes. J Res Technol Educ 54:1–17

    Article 

    Google Scholar 

  • West DM (2012) Digital schools: how technology can transform education. Brookings Institution Press

  • Yang J, Tlili A, Huang R, Zhuang R, Bhagat KK (2021) Development and validation of a digital learning competence scale: a comprehensive review. Sustainability 13:5593

    Article 

    Google Scholar 

  • Yaron D, Karabinos M, Lange D, Greeno JG, Leinhardt G (2010) The ChemCollective – virtual labs for introductory chemistry courses. Science 328:584–58

    Article 
    PubMed 

    Google Scholar 

  • Zheng B, Warschauer M, Lin CH, Chang C (2016) Learning in one-to-one laptop environments: a meta-analysis and research synthesis. Rev Educ Res 86:1052–1084

    Article 

    Google Scholar 

  • link

    Leave a Reply

    Your email address will not be published. Required fields are marked *

    Copyright © All rights reserved. | Newsphere by AF themes.