Supporting data for "Getting Students through the Gates: How Self-efficacy and Interest Trajectories Drive Learning Outcomes in Large Mathematics Courses"

Gateway courses are foundational prerequisite courses that undergraduate students must complete prior to enrolling in major courses (e.g., first-year mathematics, chemistry, psychology, statistics). Gateway courses often have high enrolment, and provide less support, structure, and feedback compared to previous experiences (e.g., secondary school). Declines in students' motivation and performance are common. This PhD project investigated two sources of engagement and motivation: self-efficacy and interest across two mathematics gateway courses. In particular, factors related to how self-efficacy and interest changed during the courses were examined across the studies. Four studies were conducted across five offerings of these two courses from 2020-2022. Participants were students enrolled in these courses. Study 1 (n=175; Sept-Dec 2020; Course 1) was conducted in an online (pandemic) setting. The interplay between students' (amounts of) self-efficacy, interest, and performances (i.e., quizzes) across the course was investigated. Study 2 (n=349; Sept-Dec 2021; Course 1) was conducted the next year, and examined how overall self-efficacy changes, and how those changes were associated with performances across a course, and interest at the end of the course. Study 3 (n=313; Sept-Dec 2021; Course 2) investigated short-term changes in interest, and how they were related to performance, and self-efficacy. Lastly, Study 4 contained two studies (n=299; n=407; Studies 4a, 4b; Courses 1 &amp; 2) that investigated the interplay between perceived difficulty on performance tasks (i.e., quizzes), short-term changes in self-efficacy, performances, and interest (in the second study).The data files are the datasets used to conduct the analyses across the four studies. These included students' responses on formative quizzes, and self-reported data on self-efficacy, interest, perceived difficulty, and gender. These data were used for quantitative analysis using MPlus and other software. Each folder contains the relevant files each study (presented in the respective chapter of the thesis).1) Chapter 3 - Study 1 contains the dataset used for the first study. This study is already published.<br>2) Chapter 4 - Study 2 contains the datasets used for the second study, including for the full model, invariance and reliability testing, and dataset for IRT.<br>3) Chapter 5 - Study 3 contains the datasets used for the third study, including for the full model and dataset for IRT.<br>4) Chapter 6 - Study 4 (Studies 4a and 4b) contains the datasets used for the last study, including those used for the full model, dataset for IRT, and perceived difficulty.

入门课程（Gateway courses）是本科学生修读专业课程前必须完成的基础先修课程，例如大一数学、化学、心理学、统计学课程。这类课程通常选课人数众多，且相较于中等教育阶段的学习经历，所能为学生提供的支持、教学结构与反馈均相对不足，学生学习动机与成绩下滑的情况较为常见。
本博士研究针对两门数学入门课程，探究了参与度与动机的两大来源：自我效能感（self-efficacy）与兴趣，并重点考察了课程期间自我效能感与兴趣的变化相关因素。研究于2020至2022年间，依托这两门课程的五次开课周期开展了四项子研究，参与者为修读该类课程的学生。
研究1（样本量n=175；2020年9月—12月；课程1）以线上（疫情期间）教学场景开展，探究了学生的自我效能感水平、兴趣与课程成绩（即测验成绩）之间的交互关系。
研究2（n=349；2021年9月—12月；课程1）于次年开展，考察了整体自我效能感的变化情况，以及这些变化与课程全程成绩、结课阶段兴趣之间的关联。
研究3（n=313；2021年9月—12月；课程2）探究了兴趣的短期变化，及其与成绩、自我效能感之间的关联。
研究4包含两项子研究（n=299、n=407；子研究4a、4b；课程1与课程2），考察了测验任务感知难度、自我效能感短期变化、成绩与兴趣（第二项子研究中）之间的交互关系。
本数据集即为用于开展上述四项子研究分析的原始数据，包含学生的形成性测验作答数据，以及自我报告的自我效能感、兴趣、感知难度与性别相关数据。这些数据通过MPlus及其他软件用于定量分析。每个文件夹对应一项子研究的相关文件，整理于该博士论文的对应章节中：
1) 第3章——研究1：包含第一项子研究使用的数据集，该研究已正式发表。
2) 第4章——研究2：包含第二项子研究使用的数据集，涵盖全模型检验、不变性与信度检验所需数据集，以及项目反应理论（IRT）分析数据集。
3) 第5章——研究3：包含第三项子研究使用的数据集，涵盖全模型检验所需数据集与项目反应理论（IRT）分析数据集。
4) 第6章——研究4（子研究4a与4b）：包含最后一项子研究使用的数据集，涵盖全模型检验所需数据集、项目反应理论（IRT）分析数据集以及感知难度相关数据集。