An Eight-Week Wait-List Controlled Classroom Protocol for Self-Regulated English Learning in University Students

Summary

This methods article describes an 8-week wait-list controlled classroom protocol for implementing, monitoring, and evaluating self-regulated English learning among university students.

Abstract

Self-regulated learning is an important component of successful language learning, but classroom-based interventions are often difficult to reproduce when instructional activities, student outputs, control conditions, fidelity procedures, and assessment rules are insufficiently described. This methods article presents an 8-week wait-list controlled classroom protocol for implementing and evaluating self-regulated English learning among university students. Students are assigned to either a structured self-regulated English learning protocol or ordinary English instruction with delayed access to the intervention materials. Although each week has a specific instructional focus, the protocol repeatedly embeds the cyclical self-regulated learning sequence of goal review, strategy use, monitoring, reflection, and adjustment. Weekly activities include self-diagnosis, measurable goal setting, strategic planning, vocabulary and reading strategy practice, writing revision, learning diaries, peer feedback, and final transfer planning. Each session generates a predefined student output, allowing fidelity, attendance, worksheet completion, adherence, protocol deviations, and contamination-control procedures to be documented. The protocol combines questionnaire-based outcomes with performance-based measures, including English achievement and writing performance, and specifies baseline assessment, stratified block randomization, blinded writing scoring, parallel testing procedures, missing-data rules, and adjusted statistical analysis. Representative results demonstrate how the protocol can be implemented, monitored, and analyzed in a classroom setting. These results are presented as illustrative implementation and outcome data, not as generalizable evidence of intervention efficacy. This protocol is suitable for researchers and instructors who require a practical, ethically acceptable, and reproducible procedure for studying self-regulated English learning in higher education.

Introduction

Self-regulated learning has become an important framework for understanding why students exposed to similar teaching conditions often show different learning trajectories. In this framework, learners are not treated as passive recipients of instruction, but as participants who set goals, select strategies, monitor their progress, and revise their behavior when learning conditions change. Zimmerman described self-regulated learners as students who actively use forethought, performance control, and self-reflection to guide learning behavior rather than depending only on external instruction¹. Pintrich further emphasized that self-regulation involves the monitoring and control of cognition, motivation, behavior, and context, which makes the construct particularly relevant to classroom-based language learning where students must coordinate effort, time, strategy use, and feedback².

The relevance of self-regulation is especially clear in university English learning. Many students know that they need to improve vocabulary, reading, writing, or communication, but their learning actions remain fragmented. A student may intend to “study harder,” yet this intention often fails to become a measurable goal, a scheduled task, a monitored learning behavior, or a revised strategy after feedback. Language-learning strategy research has long shown that learners differ not only in how much they study, but also in how they choose, combine, and evaluate strategies across tasks³. However, language classes do not always provide a reproducible structure through which such strategy use can be taught, observed, documented, and compared with ordinary classroom instruction. This creates a methodological problem: researchers may claim to study self-regulated learning, but the instructional procedure may remain too general for another classroom to reproduce.

Existing studies have clarified the measurement and instructional importance of self-regulated language learning. Validated work on foreign-language self-regulated learning strategy measurement has shown that the construct can be organized into identifiable strategy dimensions rather than treated as a single vague learning habit⁴. Research on second-language writing has also shown that self-regulated strategy instruction can support writing development by making planning, drafting, revising, and reflection more explicit in classroom practice⁵. Higher-education intervention research further suggests that the effect of self-regulated learning support depends on how the intervention is implemented, not only on whether the term “self-regulated learning” appears in the course design⁶. A classroom protocol should therefore specify what students do, when they do it, what they produce, how the control condition differs, and how researchers verify that the procedure was delivered as intended.

Several limitations remain in classroom-based self-regulated learning research. Some studies rely heavily on post-intervention questionnaires, which can show perceived changes but provide limited information about the weekly learning behaviors that produced those changes. Others describe strategy instruction but provide insufficient detail about lesson timing, worksheet structure, control-group activities, fidelity monitoring, adherence thresholds, or contamination prevention. In language-learning settings, this problem is particularly important because strategy use, motivation, anxiety, writing performance, and achievement may change at different rates. Reviews of self-regulated learning in online and higher-education environments have highlighted the need for stronger alignment between intervention design, learning-process evidence, and outcome measurement⁷. Without such alignment, it is difficult to determine whether a weak or inconsistent result reflects an ineffective theoretical approach, poor implementation, inadequate measurement, or contamination between study groups.

The present methods article addresses this gap by translating self-regulated English learning into an 8-week wait-list controlled classroom protocol with predefined weekly outputs. The protocol is not organized as a single linear sequence in which students complete one self-regulatory phase and then move permanently to the next. Instead, each week has a dominant instructional focus while preserving a recurring self-regulated learning cycle: students review or refine a goal, apply a strategy to an English-learning task, monitor their performance, reflect on the outcome, and make an adjustment for the next learning activity. This structure follows the practical implication of self-regulated strategy instruction: learners need repeated opportunities to connect a goal with a strategy, an action, feedback, and revision⁸. The weekly focus gradually shifts from self-diagnosis and goal setting to planning, strategy use, writing revision, monitoring, feedback use, and independent transfer, but the underlying cycle is repeated throughout the 8-week period.

The protocol includes a wait-list control condition to support ethical and methodologically interpretable classroom implementation. Students in the control condition continue ordinary English instruction during the 8-week period and receive access to the self-regulated learning worksheets after posttest assessment. This design allows the structured protocol to be compared with ordinary instruction while reducing the ethical concern of withholding potentially useful learning materials. Because participants may be randomized within the same classroom, the protocol includes contamination-control procedures, including separate activity periods or workspaces, restricted worksheet distribution, weekly control-class content logs, and delayed release of intervention materials. These procedures do not eliminate all risk of informal communication between students, but they make contamination visible and documentable when interpreting the representative results.

The protocol uses both self-report and performance-based outcomes. Self-regulated learning, self-efficacy, motivation, and anxiety are measured through structured questionnaires, while English achievement and writing performance provide task-based evidence of learning change. This combination is deliberate. Self-efficacy is closely linked to students’ willingness to initiate and sustain learning behavior, but confidence alone is not the same as improved performance⁹. Writing performance is also useful because it requires students to plan, organize ideas, select language, revise errors, and respond to task demands. Studies of writing strategy instruction in college settings have shown that self-regulation can be embedded in planning and revising processes rather than treated as a separate study-skills lesson¹⁰. The current protocol therefore connects self-regulated learning activities with observable English-learning tasks.

The method strengthens reproducibility through procedural controls. Baseline assessment is completed before randomization. Allocation is stratified by class and baseline proficiency. The intervention group receives a standardized weekly worksheet package, whereas the wait-list control group continues ordinary instruction without access to the structured self-regulated learning materials before posttest assessment. Writing samples are blinded before scoring. Fidelity, attendance, worksheet completion, diary completion, protocol deviations, and contamination-control indicators are recorded throughout the 8-week period. These elements are consistent with broader reporting expectations for randomized trials, where participant flow, allocation, follow-up, and analytic inclusion must be transparent¹¹. In classroom research, these controls are not merely administrative. They help distinguish the implementation of a structured learning protocol from ordinary teacher feedback, student motivation, or informal sharing of materials across groups.

The overall goal of this article is to present a reproducible classroom protocol for implementing, monitoring, and evaluating self-regulated English learning among university students. The protocol is designed for researchers and instructors who need a practical method that can be ethically implemented in real classes while still producing interpretable implementation and outcome data. It is most appropriate for university English courses in which students can complete weekly learning worksheets, baseline and posttest questionnaires, English achievement tests, and writing tasks. The protocol can also be adapted for blended or online delivery if worksheet access, timing, fidelity monitoring, contamination control, and data security are preserved. Current evidence on technology-supported self-regulated language learning suggests growing interest in such adaptable procedures, but also shows the need for clearer intervention structures and more consistent outcome reporting¹².

Protocol

The classroom implementation described in this article was reviewed and approved by the Foreign Languages Ethics Committee of Zhengzhou Shengda University (Approval No. 20260606) on June 3, 2026. Written informed consent was obtained from all participants before data collection. Participation was voluntary, and students could withdraw at any time without affecting their course grades. The wait-list control group received access to the self-regulated learning materials after the posttest assessment. The course-grading instructor did not access individual questionnaire responses, diary entries, consent decisions, or participant-level research data before finalizing course grades.

1. Prepare the classroom trial

1. Select undergraduate English classes with comparable syllabi, teaching schedules, assessment formats, weekly contact time, homework requirements, and academic calendars. Define the study as an individual-level, randomized, wait-list-controlled classroom protocol for university students enrolled in English-learning courses.
2. Use the participant flow diagram to plan screening, consent, baseline assessment, randomization, intervention delivery, posttest assessment, and analytic inclusion before recruitment begins (Figure 1).
3. Organize the 8-week protocol around a repeated self-regulated learning cycle. In each week, students review or refine a goal, apply a strategy to an English-learning task, monitor performance, reflect on the outcome, and record an adjustment for the next task. Base the sequence on cyclical models of self-regulated learning, in which learners move repeatedly through forethought, performance monitoring, and self-reflection13,14.
   CRITICAL STEP: Do not deliver the protocol as a single linear sequence in which one self-regulatory phase is completed only once. The weekly topic may change, but goal review, strategy use, monitoring, reflection, and adjustment should recur throughout the 8-week period.
4. Estimate the sample size before recruitment using the primary outcome, expected effect size, two-sided α level of 0.05, power of 0.80, and anticipated attrition. For the representative implementation, recruit 160 students.
5. Prepare the participant information sheet, consent form, demographic form, questionnaire battery, English achievement tests, writing prompts, writing rubric, weekly worksheets, learning diary, fidelity checklist, attendance log, control-class content log, contamination-control log, randomization list, codebook, and statistical script before recruitment.
6. Prepare the questionnaire battery using selected or adapted items from published self-regulated learning, foreign-language learning strategy, self-efficacy, motivation, and language-learning anxiety instruments15,16. Use a 24-item self-regulated English learning questionnaire scored on a 1–5 Likert scale to cover goal setting, strategic planning, strategy use, monitoring, and reflection. Use the 8-item English self-efficacy, motivation, and learning-anxiety scales scored on the same 1–5 format. Define reverse-coded items before data collection and calculate scale scores by averaging valid item responses.
   NOTE: The self-regulated learning measure should capture goal setting, planning, strategy use, monitoring, and reflection rather than only general learning attitude.
7. Ask two English-language education specialists to review the adapted questionnaire items for wording clarity, construct alignment, and suitability for university English learners.
8. Prepare one baseline English achievement test and one parallel posttest form. Align both forms with the same course syllabus and assessment blueprint. Match the forms by item type, number of items, skill coverage, total score, time limit, and expected difficulty. Score each form from 0 to 100.
9. Prepare two parallel English writing prompts for pretest and posttest. Match the prompts by genre, topic familiarity, expected length, response time, cognitive demand, and scoring rubric. Use different prompts at baseline and posttest.
10. Ask two English instructors who are not involved in scoring to review the achievement tests and writing prompts for content coverage, language level, topic familiarity, and task difficulty.
    CRITICAL STEP: Do not reuse the same achievement test or writing prompt at baseline and posttest. Use parallel forms to reduce practice effects while preserving comparable difficulty.
11. Prepare a 0–20 analytic writing rubric covering content relevance, organization, vocabulary use, grammatical accuracy, and task completion. Train two independent writing raters using the rubric, anchor samples, scoring examples, domain-level descriptors, and discrepancy-resolution rules.
12. Train the protocol instructor or research assistant using the weekly lesson script, required student output, timing rules, fidelity checklist, contamination-control procedure, and protocol-deviation log. Assign fidelity assessment to a trained research assistant who is not responsible for ordinary course grading. Use the same fidelity checklist for all 8 sessions.
13. Prepare the wait-list control condition before recruitment. Control-group students receive ordinary English instruction, ordinary homework, and ordinary teacher feedback during the 8-week period, but do not receive structured self-regulated learning worksheets, learning diaries, goal cards, strategy checklists, or reflection templates before posttest assessment.
14. Prepare all study materials listed in the Table of Materials and follow the enrollment, intervention, and assessment schedule shown in Table 1.
15. Store consent forms, participant code lists, questionnaires, writing files, test files, fidelity records, adherence records, control-class content logs, contamination-control logs, protocol-deviation logs, and anonymized datasets in separate secure folders.
    PAUSE POINT: The protocol may be paused after material preparation and resumed once ethics approval, instructor training, rater training, and data-security folders are complete.
16. Keep the participant identity file separate from all outcome data. Restrict access to identifiable data to the principal investigator or authorized research staff only.

2. Recruit participants and obtain consent

1. Introduce the study during a regular class session before baseline assessment. Invite students who are aged 18 years or older, enrolled in the selected English course, able to complete written English tasks and questionnaires, and willing to provide informed consent.
2. Exclude students who do not provide consent, withdraw before baseline assessment, cannot complete the 8-week study period, or cannot complete both questionnaire-based and performance-based assessments.
3. Ask a research assistant, rather than the course-grading instructor, to distribute and collect consent forms whenever possible.
4. Explain that participation is voluntary, questionnaire responses are confidential, and research participation is not part of formal course grading. Collect signed consent forms before administering any research instrument and assign each consenting student a unique participant identification code, such as SRL001, SRL002, and SRL003.
5. Record participant code, class, age, gender, major, year of study, prior English-learning experience, and baseline English proficiency category in the enrollment log. Remove students who do not consent from research data collection while allowing them to continue ordinary class activities.

3. Conduct baseline assessment

1. Conduct baseline assessment before randomization and before delivery of any self-regulated learning content. Ask students to write only their participant identification code on all forms, tests, and writing sheets.
2. Administer the demographic form, self-regulated English learning questionnaire, English self-efficacy scale, motivation scale, and learning-anxiety scale in the same sitting using consistent response instructions and 1-5 response anchors.
3. Administer the baseline English achievement test under a fixed time limit of 45 min. Administer the baseline writing task immediately after the English achievement test using the first writing prompt, an expected length of 120–180 words, and a fixed response time of 20 min.
4. Collect all forms and task sheets immediately after completion. Check participant code, completion status, and obvious duplicate entries before students leave the room. Record absent students in the baseline attendance log and exclude students without baseline data from randomization.
5. Enter baseline data into the master dataset using participant identification codes only. Double-check at least 10% of entered records against the original forms and correct all entry errors before randomization.
6. Lock the baseline dataset before generating the randomization list.
   CRITICAL STEP: Complete baseline assessment and dataset locking before randomization to prevent allocation from influencing baseline data collection or data entry.

4. Randomize participants and conceal allocation

1. Generate the randomization list after baseline data cleaning. Stratify randomization by class and baseline English proficiency category.
2. Randomize participants in a 1:1 ratio to the self-regulated learning protocol group or the wait-list control group. Use block randomization within each class and proficiency stratum. Record the block size, random seed, and software used to generate the allocation list.
3. Store the randomization file separately from baseline and posttest outcome files. Inform students of their assigned classroom activity schedule without discussing expected outcome differences.
4. Use individual-level randomization when the number of available class sections is too small to support class-level randomization. Record this design choice in the study log.
   NOTE: Randomization within the same classroom can introduce contamination if students communicate about learning materials. Use separate activity periods or workspaces, delayed worksheet release, and contamination logs to document this risk.
5. Keep the regular syllabus, ordinary instructional content, course assessment schedule, and general homework expectations comparable across groups whenever possible. Keep writing raters blinded to group allocation and time point by removing group and assessment labels from all writing files before scoring.
6. Keep the primary data analyst blinded to group labels until variable coding, missing-data rules, and the primary analysis plan are finalized.
7. Deliver structured self-regulated learning activities in separate activity periods, small-group arrangements, or online workspaces. Do not upload intervention worksheets, learning diaries, goal cards, strategy checklists, or reflection templates to shared course groups until posttest assessment is complete.
8. Ask participants not to exchange intervention worksheets or structured learning templates with wait-list control students before posttest assessment. Record suspected contamination events, including early worksheet sharing or control-group access to intervention materials.
9. Record final allocation, intervention exposure, posttest completion, and analytic inclusion in the participant flow diagram after data collection is complete17.

5. Deliver the self-regulated English learning protocol

1. Deliver one 30–45-minute structured self-regulated learning session per week over 8 consecutive weeks within or alongside the regular English course.
2. Follow the weekly classroom workflow shown in Figure 2 and use the worksheet package shown in Supplementary Table 1.
3. In every weekly session, include goal review or refinement, strategy practice, monitoring, short reflection, and next-step adjustment.
   CRITICAL STEP: Collect a predefined student output every week. The output is necessary for adherence monitoring, fidelity assessment, and protocol reproducibility.
4. Week 1: Orientation, self-diagnosis, and first learning target. Explain self-regulated English learning as a repeated cycle of goal setting, strategy selection, monitoring, reflection, and adjustment. Ask students to review their English learning habits, strengths, difficulties, obstacles, and previous strategy use. Each student completes a learning profile sheet with one target learning problem and one preliminary strategy.
5. Week 2: Goal setting and goal-checking method. Review the Week 1 target problem and preliminary strategy. Ask students to convert one broad English learning aim into a measurable weekly goal. Each goal card includes the target task, learning time, expected output, deadline, checking method, and adjustment plan.
6. Week 3: Strategic planning, time management, and obstacle response. Review the Week 2 goal card. Ask students to divide the weekly goal into three to five smaller tasks, assign each task to a day and time slot, include vocabulary, reading or listening, and writing or speaking practice, and identify one obstacle, response, and adjustment.
7. Week 4: Vocabulary and reading strategy practice. Review the Week 3 study plan. Demonstrate retrieval practice, spaced review, and reading annotation using a short vocabulary list and a short English paragraph. Students submit an annotated reading sample and one strategy plan.
8. Week 5: Writing strategy cycle. Review the Week 4 strategy plan. Introduce the plan-draft-revise-reflect writing cycle. Students plan a short paragraph, draft it, revise it using the analytic writing rubric, and write one reflection identifying a useful strategy, a recurring writing problem, and one revision target.
9. Week 6: Monitoring and self-recording. Review the Week 5 revision target. Students record daily learning time, task completion, strategy used, obstacle encountered, and adjustment made. Require at least three diary entries and allow students to omit any private entry they do not wish to share.
10. Week 7: Feedback use and peer calibration. Review Week 6 diary entries. Students use the writing rubric to score a practice paragraph, discuss score differences, provide rubric-guided peer feedback, revise one sentence or paragraph, and write one feedback-use statement.
11. Week 8: Reflection, transfer planning, and closure. Students review their learning profile, goal cards, study plans, strategy sheets, writing revisions, diary entries, peer-feedback records, and previous adjustments. They identify one effective strategy, one ineffective strategy, one persistent obstacle, one future learning goal, and one planned monitoring method.
12. Collect all final learning materials before posttest assessment and provide the wait-list control group with access to the full worksheet package only after posttest data collection is complete.

6. Deliver the wait-list control condition

1. Continue ordinary English instruction for the wait-list control group during the 8-week study period. Keep the syllabus, weekly teaching content, homework expectations, teacher feedback format, and assessment schedule comparable with the regular course activities received by the protocol group.
2. Do not provide structured self-regulated learning worksheets, learning diaries, goal cards, strategy checklists, peer-feedback templates, or reflection sheets to the wait-list control group before posttest assessment.
3. Record weekly control-class content, homework, attendance, teacher feedback format, and any exposure to self-regulated learning materials in the control-class content log.
4. Avoid uploading intervention materials to shared course groups before posttest assessment. Record any early exposure or suspected material sharing in the contamination-control log.
   CRITICAL STEP: Keep the control condition as ordinary English instruction rather than an unstructured or inactive condition. This allows the protocol group to be compared with usual classroom practice while preserving delayed access for control-group students.
5. Provide the full self-regulated learning worksheet package to the wait-list control group only after all posttest data have been collected.

7. Conduct posttest assessment

1. Conduct posttest assessment during Week 8 after completion of the final protocol session.
2. Administer posttest assessment to both groups within the same week using the same instrument order, instructions, time limits, classroom rules, and response format used at baseline.
3. Administer the self-regulated English learning questionnaire, English self-efficacy scale, motivation scale, learning-anxiety scale, parallel English achievement test, and posttest writing task.
4. Use the second writing prompt for posttest writing. Keep the genre, expected length, response time, scoring rubric, and task difficulty comparable with the baseline writing task.
   CRITICAL STEP: Use the parallel posttest achievement form and second matched writing prompt rather than repeating the baseline test or baseline prompt.
5. Record students who are absent from posttest assessment and mark the corresponding posttest outcomes as missing. Do not replace missing posttest values with artificial values.
6. Collect all posttest materials, verify participant codes and completion status, and store all files by participant identification code.
7. Lock the posttest dataset after completion checks and before group-comparison analysis.

8. Score outcomes and process data

1. Score all outcomes according to the definitions, score ranges, scoring rules, and timing shown in Table 2.
2. Score questionnaire outcomes by averaging valid item responses within each scale. Reverse-code items only when reverse coding is specified in the scale documentation.
3. Calculate a scale score only when at least 80% of items in that scale are valid. Mark the scale score as missing when more than 20% of items are missing.
4. Score English achievement tests from 0 to 100 using the prespecified answer key and scoring guide.
5. Remove group labels from all writing files before scoring. Rename writing files using coded identifiers that do not reveal allocation.
6. Train two independent raters with the analytic writing rubric, anchor samples, scoring examples, and discrepancy rules before formal scoring.
7. Ask both raters to score all writing samples independently using the 0–20 analytic rubric. Record domain scores for content relevance, organization, vocabulary use, grammatical accuracy, and task completion.
8. Calculate inter-rater reliability using a two-way random-effects intraclass correlation coefficient for absolute agreement. Report reliability for the total writing score and inspect domain-level agreement.
9. Resolve total-score discrepancies greater than 3 points through discussion or third-rater adjudication. Use the mean of the two rater scores as the final writing score after discrepancy resolution.
   CRITICAL STEP: Do not score writing outcomes by a single unblinded instructor. Use independent scoring and report inter-rater reliability.
10. Check all questionnaire, test, writing, fidelity, adherence, and process scores against allowable ranges before analysis.

9. Monitor fidelity, adherence, and protocol deviations

1. Complete one fidelity checklist after each intervention session. The checklist should be completed by a trained research assistant who is not responsible for ordinary course grading.
2. Record whether the planned weekly objective, instructor explanation, student activity, student output, timing requirement, and collection procedure were completed.
3. Rate each session on a 1-5 fidelity scale, where 1 indicates very low fidelity, and 5 indicates full completion of planned components.
4. Record attendance, worksheet completion, diary completion, feedback-sheet completion, final-reflection completion, contamination events, and protocol deviations each week.
5. Calculate attendance as the number of attended sessions out of 8. Calculate diary completion rate as completed diary entries divided by expected diary entries.
6. Define adequate intervention exposure as attendance at least 6 of 8 sessions for per-protocol sensitivity analysis.
7. Record protocol deviations immediately after each session, including class cancellation, shortened session time, missing worksheet, instructor replacement, technical failure, unexpected classroom disruption, or early material exposure.
8. Record fidelity and adherence indicators using the criteria shown in Table 3.

10. Construct the analytic dataset

1. Create one row for each randomized participant.
2. Include participant code, class, randomization block, group allocation, age, gender, major, baseline English proficiency category, and posttest completion status.
3. Include intervention exposure and process variables, including attendance, worksheet completion, diary completion rate, fidelity rating, contamination status, and protocol-deviation status.
4. Include pretest and posttest scores for self-regulated English learning, English self-efficacy, motivation, learning anxiety, English achievement, and writing performance.
5. Create change-score variables for descriptive reporting by subtracting pretest scores from posttest scores.
6. Create an all-randomized dataset containing every randomized participant and a primary available-case analysis dataset containing participants with valid baseline and posttest values for the analyzed outcome.
   NOTE: Do not describe an available-case primary analysis as a complete intention-to-treat analysis. Use the all-randomized dataset to describe allocation, follow-up, missingness, and sensitivity analyses.
7. Create a per-protocol dataset including participants who completed posttest assessment and met the predefined intervention exposure threshold.
8. Save the final anonymized dataset in spreadsheet and statistical software formats. Save a codebook defining every variable, coding rule, score range, missing-value rule, and analytic role.
9. Maintain an analysis-readiness checklist documenting dataset lock date, missing-data review, range checks, rater reliability results, fidelity summary, contamination log review, and final variable names.

11. Analyze the data

1. Summarize participant flow, baseline characteristics, intervention exposure, posttest completion, missingness, and analytic inclusion.
2. Report baseline characteristics by group without relying on baseline significance testing as the main evidence of randomization quality.
3. Analyze the primary outcome using analysis of covariance, with posttest self-regulated English learning score as the dependent variable, group as the independent variable, and baseline self-regulated English learning score as the covariate.
4. Include class as a fixed effect in the main model to account for classroom context. Use a mixed-effects model as a sensitivity analysis when the number of classes is sufficient to support class-level random effects¹⁸.
5. Analyze secondary outcomes using the same adjusted approach. Fit separate models for posttest English self-efficacy, motivation, learning anxiety, writing score, and English achievement score.
6. Before interpreting ANCOVA results, assess linearity between baseline and posttest scores, homogeneity of regression slopes, residual distribution, homoscedasticity, influential observations, and model fit.
   CRITICAL STEP: Check the group-by-baseline score interaction before final ANCOVA interpretation. A meaningful interaction indicates that the homogeneity-of-regression-slopes assumption may not hold.
7. Report adjusted mean difference, 95% confidence interval, p value, and effect size for each outcome. Conduct descriptive change-score analysis by reporting pretest mean, posttest mean, mean change, and standard deviation of change by group.
8. Conduct the primary analysis using participants with valid baseline and posttest data for the analyzed outcome. If posttest missingness exceeds 5%, conduct multiple-imputation sensitivity analysis under a missing-at-random assumption, including group, class, baseline score, demographic variables, and available outcome variables in the imputation model.
9. Conduct per-protocol sensitivity analysis using participants who meet the predefined exposure threshold.
10. Examine associations between adherence indicators and self-regulated learning improvement within the protocol group as exploratory process evidence. Do not interpret adherence associations as causal effects because adherence is not randomized.
11. Use two-sided tests and set the significance level at 0.05 for the primary outcome. Interpret secondary outcomes as supportive rather than confirmatory endpoints.

12. Manage withdrawal, confidentiality, and delayed access

1. Allow students to withdraw from the study at any time without academic penalty. Record withdrawal, absence, discomfort, or discontinuation in the study log.
2. Stop research participation for any student who withdraws consent. Retain previously collected anonymized data only if this procedure is stated in the consent form and approved by the ethics committee.
3. Remove all direct identifiers from the analytic dataset and store the participant code list separately from questionnaire, writing, diary, and test data. Provide delayed access to the full self-regulated learning package for the wait-list control group after posttest assessment.
4. Archive anonymized datasets, codebooks, scoring rubrics, fidelity checklists, contamination-control logs, protocol-deviation logs, and statistical scripts as supplementary files where permitted by ethics approval and journal policy.

Results

Participant flow, baseline characteristics, and posttest completion

The representative dataset included 180 students assessed for eligibility. Twenty students were excluded before randomization: 8 did not meet the inclusion criteria, 9 declined participation, and 3 were unavailable for the full 8-week follow-up period. The final randomized sample included 160 students, with 80 assigned to the self-regulated learning protocol group and 80 assigned to the wait-list control group...

Discussion

This methods article presents a reproducible classroom protocol for implementing self-regulated English learning among university students under randomized, wait-list controlled conditions. The protocol translates self-regulated learning from a broad theoretical construct into observable classroom actions by converting goal setting, strategic planning, strategy use, monitoring, feedback uptake, and reflection into weekly student outputs. This structure is important because classroom-based intervention research requires v...

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
Item name	Source / responsible unit	Specification	Purpose in the protocol
Analytic writing rubric	Research team	0–20 total score; five 0–4 domains	Used to score content relevance, organization, vocabulary use, grammatical accuracy, and task completion.
Baseline and posttest English achievement tests	Research team or course teaching unit	Two parallel 40–50 min tests; scored from 0 to 100	Used to assess course-aligned English achievement. The posttest form is matched to the baseline form by item type, length, topic coverage, and expected difficulty.
Baseline and posttest writing prompts	Research team	Two parallel 20 min writing tasks; expected length 120–180 words	Used to assess writing performance. The posttest prompt does not repeat the baseline prompt but uses the same genre, response time, and expected difficulty.
Blinded writing-sample folder	Research team	Writing files labeled by participant ID and time point only	Used to store baseline and posttest writing samples without group labels before independent scoring.
Control-condition and contamination-control logs	Research team	Control-class content log, worksheet distribution log, and contamination-control log	Used to document ordinary instruction in the wait-list control group, delayed access, restricted worksheet distribution, and possible cross-group exposure.
Data-entry and analysis dataset template	Research team / data manager	Spreadsheet with fixed variable names, valid ranges, coding rules, and missing-value rules	Used for data entry, range checking, scale scoring, missing-data review, and construction of the analytic dataset.
Demographic questionnaire	Research team	Participant-code-based form	Used to collect age, gender, major, year of study, class ID, prior English-learning experience, and baseline English proficiency category.
Eight-week self-regulated learning worksheet package	Research team	W1 learning profile, W2 goal card, W3 study plan, W4 reading/vocabulary strategy sheet, W5 writing cycle worksheet, W6 learning diary, W7 peer-feedback sheet, and W8 final reflection sheet	Used to deliver the structured self-regulated learning protocol and generate weekly student outputs for adherence monitoring.
Eligibility and enrollment form	Research team	Screening and enrollment record	Used to confirm eligibility, consent status, class, demographic characteristics, baseline proficiency category, and participant identification code.
English learning anxiety scale	Research team; adapted from language-learning anxiety measures	8 items; 1–5 Likert scale	Used to assess English learning anxiety. Reverse-coded items are defined before data collection, and higher final scores indicate higher anxiety.
English learning motivation scale	Research team; adapted from learning motivation measures	8 items; 1–5 Likert scale	Used to assess effort, persistence, perceived value, and willingness to continue English learning.
English self-efficacy scale	Research team; adapted from English-learning self-efficacy measures	8 items; 1–5 Likert scale	Used to assess confidence in vocabulary learning, reading comprehension, writing, task completion, and independent English study.
Fidelity and adherence monitoring forms	Research team	Fidelity checklist, attendance record, worksheet completion record, and diary completion record	Used to record session fidelity, attendance, worksheet completion, diary completion, exposure level, and per-protocol eligibility.
Participant information sheet and written consent form	Research team	Ethics-approved study information and consent documents	Used before data collection to explain study purpose, voluntary participation, confidentiality, withdrawal rights, delayed access, and the statement that participation does not affect course grades.
Protocol deviation and posttest completion logs	Research team	Deviation record and posttest completion record	Used to document deviations, corrective actions, posttest questionnaire completion, posttest achievement-test completion, and posttest writing-task completion.
Randomization list	Statistician / data manager	Stratified block randomization by class and baseline proficiency category	Used to assign participants 1:1 to the self-regulated learning protocol group or wait-list control group after baseline data cleaning.
Rater training packet	Research team	Rubric, scoring guide, anchor samples, example scores, and discrepancy rules	Used to train independent writing raters before formal scoring and to support consistency in writing assessment.
Secure electronic storage	Institution	Encrypted institutional project folder	Used to store consent forms, restricted participant code files, raw data, anonymized data, writing samples, scoring files, logs, statistical scripts, and archived reproducibility materials.
Self-regulated English learning questionnaire	Research team; adapted from published self-regulated learning instruments	24 items; 1–5 Likert scale	Used to assess goal setting, strategic planning, strategy use, monitoring, and reflection. Scale scores are calculated by averaging valid item responses.
Statistical packages	R package set	tidyverse, emmeans, effectsize, mice, lme4, psych, irr, gtsummary or flextable	Used for data management, adjusted group means, effect sizes, multiple imputation, mixed-effects sensitivity analysis, ICC calculation, and manuscript table generation.
Statistical software	R Foundation for Statistical Computing	R version 4.4.2 or later	Used for descriptive statistics, reliability analysis, ANCOVA, sensitivity analysis, multiple imputation, and table export.
Weekly lesson script package	Research team	Eight weekly lesson scripts	Used to standardize session objective, timing, instructor explanation, student task, required output, and fidelity monitoring across Weeks 1–8.