Agentic education · Learning science

Actionable companion · Learning design & outcomes

Learning with agency: Network analysis investigating the differentiation of achievement goal orientations in junior high school

AI-assisted editorial implementation guide, separate from the original research. Proposed actions are not claims or recommendations attributed to the source authors. No independent peer review of this guide is asserted.

Evidence and context

Title and abstract screening; stage labels describe reported settings, not verified numerical ages. Design labels require full-text appraisal. Reported stage(s): Secondary school. Verify the participant population and task before transferring the findings.

Original authors’ abstract, reproduced under the linked source license:

Achievement goal orientation theory has become popular, as it interprets students’ academic attitudes and behavior. The present research aims to investigate the variation in teachers’ perceived goals in relation to achievement goals in different grades, as well as the emergence of the multiple goal theory. Participants were junior high school students who responded to a self-report questionnaire. The instrument used was the Patterns of Adaptive Learning Scales (PALS). The results revealed that mastery and performance goals behave as a network of interacting variables that essentially represent their coexistence, as well as their individual variations and specificities in relation to other variables. However, a significant distinction between mastery goals and perceived mastery goals with performance goals and perceived performance goals became apparent for each individual grade. The present research contributes to the theoretical development of the field, while in practice it highlights the combination of goals in school reality.

What kind of evidence is this?

Intelligent tutoring & adaptive learning · Survey / observational study

Stage: Secondary school. Screening labels describe reported context and study-design language. They are not a risk-of-bias rating or proof of effectiveness for an age band.

Study methods · source passage

Achievement goal orientation theory has become popular, as it interprets students’ academic attitudes and behavior. The present research aims to investigate the variation in teachers’ perceived goals in relation to achievement goals in different grades, as well as the emergence of the multiple goal theory. Participants were junior high school students who responded to a self-report questionnaire. The instrument used was the Patterns of Adaptive Learning Scales (PALS). The results revealed that mastery and performance goals behave as a network of interacting variables that essentially represent their coexistence, as well as their individual variations and specificities in relation to other variables. However, a significant distinction between mastery goals and perceived mastery goals with performance goals and perceived performance goals became apparent for each individual grade. The present research contributes to the theoretical development of the field, while in practice it highlights the combination of goals in school reality.

Limitations and uncertainty · source passage

This study has some limitations. First, the sample size was a major limitation, as there was a larger sample of students in the 7th and 8th grades and a smaller sample in the 9th grade. Another limitation was that the instruments used were self-report questionnaires. Self-reporting instruments have several drawbacks ( Stamovlasis, 2016). Nevertheless, the data collection was conducted at a given point in time (cross-sectional study), with all the disadvantages that this can have. A further limitation is that no emphasis was placed on the school context, according to which the variables under investigation were formed.

Design the system before the pilot

Document the learner model, mastery rule, hint sequence and adaptation signal. Compare adaptive routing with the same content in a non-adaptive sequence. Check whether early errors lead to persistent low-expectation pathways.

  • Specify a measurable learning objective, a comparator and a task without tool assistance before adopting a system.

A 90-day district pilot

  1. Days 1–15 · Appraise. Have the curriculum lead and a teacher read the methods and limitations. Record the study design, sample, comparator, outcomes and evidence gaps. Define a local question that the study can help inform.
  2. Days 16–30 · Design. Ask learners to attempt a problem unaided, compare an agent hint, explain a revision and verify the final reasoning against a trusted source. Make the permitted use explicit for each assignment. Name an accountable owner and set the baseline, success threshold and budget before implementation.
  3. Days 31–60 · Test. Start with a small voluntary cohort, preserve an accessible non-AI route and require teacher review. Use synthetic or de-identified examples; approve data handling and tool terms through district processes.
  4. Days 61–90 · Decide. Measure unaided transfer and delayed retention, calibration of confidence and the ability to identify an incorrect AI explanation. Record whether help-seeking becomes answer copying. Compare with baseline, document uncertainty and stop or revise if learning worsens, access is unequal or critical errors persist.

The board decision brief

Report the learning problem, evidence quality, participating population, total cost including review time, measured benefit, errors, access differences and remaining uncertainties. Make a dated recommendation to stop, revise or expand. A positive perception survey alone does not establish learning improvement.

Attribution and reuse

Georgia Stavropoulou; Maria Gkevrou; Dimitrios Stamovlasis. Network analysis investigating the differentiation of achievement goal orientations in junior high school. F1000Research (2025-01-01). https://doi.org/10.12688/f1000research.167284.2

Companion prepared 2026-10-30. Original authorship and DOI are preserved. The abstract is an attributed source extract; the implementation plan is new AI-assisted editorial material, offered under the same CC BY 4.0 license. This guide has not undergone independent peer review.