Technology For Math Instruction
In this article I will review the findings for the 2022, meta-analysis on technology and math instruction, by Ran, Et al. This meta-analysis examined 77 studies on the topic. All studies had a control group, reported sufficient statistical outcomes, were written in English, and included students ranging from Kindergarten to Grade 12. The meta-analysis excluded all studies from before the year 2000, to ensure relevance to today's technology. The authors also did a sub-analysis on the dates of studies, comparing the effect sizes of older studies to newer ones. There were no meaningful differences within this sub-analysis.
Meta-Analysis Interventions Glossary:
Technology used to improve collaboration and communication for students showed the largest effects. Interventions that fit into this category did things like provide students virtual classrooms, interaction opportunities between the teacher and classmates, or interventions that greatly “extend students' learning opportunities beyond the physical classrooms.” These results might lend credence to the argument of virtual classrooms like Google Classroom, being used not as a replacement for the physical classroom, but as an addendum to.
Problem Solving Interventions:
Problem solving interventions were taught using technology, by providing students with problem solving questions on a computer, that also included visuals to enhance the students conceptual understanding of the problem.
Conceptual Understanding Interventions:
Software programs that were designed to enhance students' conceptual knowledge. The authors specifically cited geometry programs such as GeoGebra as having the largest effect.
Adaptive Processes Interventions:
Interventions, in which the software automatically adjusted the difficulty and type of problems to students’ needs.
Interventions, in which the technology was used to monitor student learning, but not matched with any specific follow up instruction.
The overall impact of technology interventions for math instruction was very low; indeed, the mean effect size found in this meta-analysis was barely statistically significant. However, this is consistent with other meta-analyses on the topic. John Hattie’s meta-analysis of the topic, which included 911 total studies, found similar results, with a mean ES of .35. What likely matters is not whether or not technology is used, but rather how it is used. Moreover, if we look at this study's sub analysis of intervention duration, we find that the longer an experiment continued the less effective technology was. This possibly suggests that the primary usefulness of technology in the classroom, lies only in its novelty effect. One finding of this experiment that surprised me was the futility in using technology for adaptive processes, as adaptive processes by definition seek to do what all good teachers should strive to do, individualize the instruction. One flaw in the programmining studied, might be that while the software adapted questions, it may not have provided additional explicit instruction, where the students needed it. Overall, within this meta-analysis, we see weak results for using technology to assist with math instruction, with the only meaningful outcomes found for collaborative technology interventions.
Ran. (2022). A meta‐analysis on the effects of technology’s functions and roles on students’ mathematics achievement in K‐12 classrooms. Journal of Computer Assisted Learning., 38(1), 258–284.
J, Hattie. (2022). Meta-X. Visible Learning. Retrieved from <https://www.visiblelearningmetax.com/influences>.