Measuring Learning Effectiveness: A New Look at No-Significant-Difference Findings
Ernest H. Joy; Federico E. Garcia · 2019 · Online Learning
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
The finding, in one line
“Much of the literature purports to have found no significant difference in learning effectiveness between technology-based and conventional delivery media.”
Abstract
Researchers, instructional designers and consumers of ALNs must be cautious when interpreting results of media comparison studies. Much of the literature purports to have found no significant difference in learning effectiveness between technology-based and conventional delivery media. This research, though, is largely flawed. In this paper, we first outline the philosophical positions of the opposing sides of an intense debate in the literature as to whether delivery media alone influence learning outcomes. We then select at random several representative media comparison studies to illustrate
Abstract by Ernest H. Joy; Federico E. Garcia, Online Learning (2019) — licensed CC BY 4.0.
About to run something similar?
Run an AI Precheck on your own design to catch failure modes like this one before you spend the time. Your first desk check is free.
Related failures
Investigating Variation in Replicability
Negative / Null Result ReportMany Labs 2: Investigating Variation in Replicability Across Samples and Settings
Failed Experiment ReportGetting Ahead in the Communist Party: Explaining the Advancement of Central Committee Members in China
Negative / Null Result ReportReducing implicit racial preferences: II. Intervention effectiveness across time.
Negative / Null Result ReportTHE IMPACT OF IMMIGRATION ON THE STRUCTURE OF WAGES: THEORY AND EVIDENCE FROM BRITAIN
Negative / Null Result ReportRevisiting the Marshmallow Test: A Conceptual Replication Investigating Links Between Early Delay of Gratification and Later Outcomes
WASTE indexes this work — it does not host or republish it. Failure-type classification is automated and approximate.
Metadata source: OpenAlex · DOI 10.24059/olj.v4i1.1909
