Richard E. Clark

Introduces the BEC framework for diagnosing and addressing effort‑based motivation problems. Focuses on four factors—values, self‑efficacy, emotions, and attribution errors—and offers measures and evidence‑based strategies to help learners start, persist, and invest adequate mental effort.

Argues that minimally guided approaches overload working memory and ignore human cognitive architecture. Reviews decades of evidence showing fully guided instruction is more effective and efficient for novices; benefits of reduced guidance emerge mainly for learners with high prior knowledge. Summarizes design models that support guidance.

This article argues that minimally guided instructional approaches conflict with human cognitive architecture and decades of empirical evidence. It synthesizes research showing that guidance-heavy methods (e.g., explicit instruction, worked examples) are generally more effective and efficient for novice learners, and that the advantages of reduced guidance emerge only when learners already possess high prior knowledge to generate internal guidance. The paper outlines implications for designing instruction aligned with cognitive load theory. citeturn17search4

Meta‑analysis of adequately designed field and lab studies shows incentive programs yield an average 22% performance gain, with team‑directed incentives especially effective. Effects were generally robust across settings, study types, and outcome measures, while some program designs produced larger gains than others.

Presents the four‑component instructional design (4C/ID) model for complex skill acquisition. Training blueprints integrate: learning tasks, supportive information, just‑in‑time information, and part‑task practice. The article explains links to cognitive processes, offers design methods for each component, and illustrates with a worked example.

Synthesizes theoretical and methodological distinctions between academic self‑concept and self‑efficacy. Finds that, although related, self‑efficacy tends to show stronger predictive and explanatory power for academic performance and persistence, while self‑concept more strongly relates to affective outcomes. Offers directions for future research.

Clarifies arguments about media effects on learning, motivation, and efficiency and responds to critiques. Clark reiterates that learning outcomes are driven by instructional methods, not by the medium of delivery, and addresses common reactions and criticisms to this claim.

Reanalysis of a sample of CBI studies suggests reported achievement gains are overestimated due to uncontrolled instructional method differences and related confounds, rather than the computer medium itself. Argues comparable gains could be achieved with other media delivering the same methods.

Reviews meta‑analyses and studies of media’s influence on learning and concludes that specific delivery media do not, by themselves, produce learning gains. Apparent benefits commonly arise from differences in instructional methods or novelty effects. The article critiques media‑attribute theories and recommends refocusing research on instructional methods rather than media per se.