From leadership research to district action: Successful student learning outcomes in Moroccan higher education: Causal configurations of pedagogical, motivational, and ICT conditions using fuzzy-set Qualitative Comparative Analysis (fsQCA)

AI-assisted editorial implementation guide. Proposed district actions are separate from the original authors’ findings and recommendations. Independent peer review of this guide is not asserted.

Read source Search paper agent CC BY 4.0

Evidence and transfer

Education-related source: verify which participants, institutions and outcomes were actually studied before district adoption. Source publication type: research-article. License and identity checks do not establish study quality or causality.

Original authors’ abstract, reproduced under the source license:

As the demand for better educational quality and improved student performance grows, institutions face increasing challenges in making their teaching methods more effective to ensure successful learning outcomes. Most practical recommendations tend to focus on isolated effects, but learning success usually results from interconnected factors that work together. Drawing on constructivist Learning Theory, this study examines pedagogical and motivational factors that can positively impact learning results in higher education within Moroccan universities. The main goal is to identify and evaluate the nonlinear individual effects and the interactive causal configurations involving multiple conditions, such as teacher motivation, pedagogical leadership, self-efficacy, instructional innovation, ICT use, and student motivation, on learning outcomes. Empirical data were gathered through a questionnaire completed by 349 Moroccan university students, using measurement scales for key variables. The analysis employed the fuzzy-set Qualitative Comparative Analysis (fsQCA) method, which helps identify different combinations and causal pathways that lead to high academic achievement. Findings suggest that excellent learning outcomes are not caused by a single factor but by the interaction of several interdependent conditions. Different “recipes” can produce similar strong results. Certain combinations, especially those with strong teacher motivation, effective leadership, and strategic ICT use, proved to be reliable configurations, showing that technology is most impactful when integrated into supportive pedagogical and motivational environments. These results can help redefine and evaluate integrated educational policies, considering the complex interactions among individual, pedagogical, and technological factors. This approach promotes more effective and equitable learning environments through coherent bundles of mutually reinforcing interventions, instead of isolated efforts. Ultimately, this research enables educators and policymakers to develop more targeted strategies, utilize resources more efficiently, and improve overall educational effectiveness.

Study methods

Data collection is a crucial step in the in-depth analysis of the configurations that lead to student learning outcomes. This is especially true when considering the importance of the methodology employed, particularly through the Qualitative Comparative Analysis (fsQCA) approach. To successfully execute this essential phase and ensure effective information gathering, a detailed questionnaire was designed and distributed to Moroccan students. This questionnaire aims to collect relevant, meaningful, and diverse information to illuminate learning dynamics and enhance understanding of the factors influencing students’ academic performance.

Limitations

The current study has several notable limitations that should be recognised, as they hinder the generalizability of the results. First, the study’s exclusive focus on institutions in Morocco raises questions about whether similar outcomes would occur in other contexts, such as other nations or educational fields. Future research could examine the consistency of these findings across a broader range of settings using appropriate data collection methods and more varied comparative samples, thereby enhancing our understanding of the results. Second, while student perspectives and evaluations are crucial indicators of instructional effectiveness, other factors related to student behaviours, activities, and engagement may also contribute to disparities in learning outcomes. It is recommended to use other appropriate statistical or predictive techniques to expand the existing analysis of the effectiveness of higher education programs. This investigation could yield further insights and enrich our comprehension of the involved dynamics.

A 90-day district inquiry

Days 1–15 · Appraise. Read the source methods, recruitment, comparator, outcomes and limitations. Record how the study setting differs from your district and which claim the design can support.
Days 16–30 · Design. Choose one school improvement question with teachers. Protect a short shared planning cycle, agree an instructional change and use a common rubric for examining student work. Agree participation, privacy protections, baseline and stopping rules before starting.
Days 31–60 · Observe. Collect the pre-agreed measures, keep a log of implementation changes and invite confidential voluntary feedback. Preserve existing support for staff and learners.
Days 61–90 · Decide. Review implementation fidelity, teacher time and independently scored student work against a recorded baseline. Examine access differences and competing explanations before attributing changes to leadership. Make a dated decision to stop, revise or extend the inquiry.

Board decision brief

Present the local problem, source setting, evidence limits, intervention, responsible owner, total cost, measured changes and uncertainty. Separate staff perceptions, implementation measures and student learning outcomes.

Attribution and reuse

Razzouki mustapha; Wided Ragmoun; Salah Ben Hammou. Successful student learning outcomes in Moroccan higher education: Causal configurations of pedagogical, motivational, and ICT conditions using fuzzy-set Qualitative Comparative Analysis (fsQCA). PLOS One (2026-04-21). https://doi.org/10.1371/journal.pone.0347120

Prepared 2026-11-07. Source authorship and DOI are preserved. The abstract and source passages are attributed extracts; this editorial guide is offered under the same CC BY 4.0 license.