A meta‐analysis on the effects of technology's functions and roles on students' mathematics achievement in K‐12 classrooms

• Published in: Journal of computer assisted learning 2022-02, Vol.38 (1), p.258-284
• Main Authors: Ran, Hua, Kim, Nam Ju, Secada, Walter G.
• Format: Article
• Language: English
• Subjects: Adaptive Testing; Blended Learning; CAI; Classrooms; Collaboration; Computer assisted instruction; Concept Formation; Cooperative Learning; COVID-19; Educational Environment; Educational Technology; Elementary Secondary Education; instruction design; Interpersonal Communication; Intervention; K‐12; Learning; Learning Processes; Mathematical analysis; Mathematical Concepts; Mathematics; Mathematics Achievement; Mathematics Education; Mathematics Instruction; Meta-analysis; Online Courses; Pandemics; Problem Solving; Program Effectiveness; School Closing; Software development; Student Evaluation; Students; Teachers; Teaching Methods; technology roles; Technology Uses in Education; Technology utilization
• ISSN: 0266-4909; 1365-2729
• DOI: 10.1111/jcal.12611

Background With the recent pivot to online instruction and/or to mixed online/face‐to‐face (i.e., hybrid) models of teaching necessitated by the novel coronavirus pandemic, the uses of technology to support instruction would seem to have great importance. Whereas effective integration of technology in mathematics classrooms requires recognition of students’ needs and instructional goals that technology could fulfill, very few comprehensive meta‐analytical studies have focused on the roles of instructional technology in support of specific learning goals. Objectives In this meta‐analysis, we investigated and reviewed the roles and affordances of technology in mathematics instruction and its effects on students' mathematics achievement. Methods Cross‐searching multiple bibliographic databases generated a total of 3276 potentially relevant full‐text studies. After applying a series of inclusion/exclusion criteria, we kept 77 studies with 151 effect sizes. Two researchers then coded for seven sets of study features and student characteristics: technology roles, publication‐related features (years and resources), research design, sample size, grade levels, duration of interventions, and types of the testing instruments. The coding achieved acceptable levels of inter‐rater reliabilities. Since effect sizes varied across studies and student populations, random‐effects models were used for overall effect estimates and moderator analyses. Results and conclusions Overall, this meta‐analysis revealed a small, positive, and statistically significant effect of technology on students' mathematics achievement with an average Hedges' s g (ḡ) of 0.23. The largest significant moderator effects were found when technology was used to design and support collaborative and communicative environments (ḡ = 0.49); the next‐largest moderator effects were found when using technology as supports for problem‐solving (ḡ = 0.39), followed by the roles of as supports for conceptual development (ḡ = 0.31) and as adaptive mathematics practices (ḡ = 0.28). This study also found that the effects of technology were differentiated as a function of publication resources, research design, duration of intervention, and the testing instrument. Major takeaways Focusing on the roles and functions of technology, this study can contribute to guide potential synthetical studies as well as the future design of educational technology. In particular, technology is used effectively when it is used (a) to cr