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Abstract

This study employed a Convergent Mixed-Methods Design to examine how mobile gaming influences students’ behaviour, study habits, physical well-being, and academic obligations within a senior high school educational context. The quantitative component involved 58 Grade 11 students from Section X in the Philippines who answered a 10-item Likert-scale survey assessing gaming habits, academic distractions, sleep problems, physical symptoms, and coping strategies. Data were analyzed using weighted means, frequency distributions, and Pearson’s correlations. The qualitative component consisted of semi-structured interviews with ten purposively selected participants. The thematic analysis revealed three major themes: (1) gaming for enjoyment and escape, (2) physical discomfort and sleep loss, and (3) difficulty managing academic responsibilities alongside failed attempts at self-regulation. Findings indicated that greater gaming involvement was associated with reduced focus, sleep deprivation, decreased motivation, and neglect of academic tasks. Quantitative results revealed a moderate negative relationship between mobile game addiction and academic performance (r = −.52, p < .001). Qualitative narratives further explained how sleep loss, cognitive fatigue, and reinforcement-driven habits contributed to academic disengagement despite students’ awareness of negative consequences. The study highlights the importance of digital literacy programs, structured guidance interventions, and school-based strategies that promote responsible gaming habits and academic self-regulation among learners.

Author Biography

Mhel Cedric D. Bendo, Polytechnic University of the Philippines

Mhel Cedric D. Bendo is a student researcher specializing in educational psychology, curriculum and instruction, educational measurement and evaluation, psychometrics, educational technology, and business and financial technology (FinTech). He is pursuing a Bachelor of Science in Entrepreneurship at the Polytechnic University of the Philippines. As of 2026, he is a member of the Editorial Board of SIAR Publications, an Editorial Board Member of the International Journal of Multidisciplinary Research and Exploration (IJMRE), and an Editorial Board Member and Review and Technical Committee Member of the International Journal of Advanced Multidisciplinary Application (IJAMA), where he contributes to peer review, subject-area feedback, manuscript evaluation, and research assessment. He also serves as a Technical Editor for the Journal of Student-Run Clinics (JSRC), contributing to editorial review processes and the technical evaluation of submitted manuscripts. He is an invited peer reviewer for international peer-reviewed journals, including Cogent Education (Taylor & Francis), a peer-reviewed journal published by a leading global academic publisher, contributing to the evaluation of scholarly work in education and interdisciplinary research. His reviewing contributions cover education, psychology, artificial intelligence in education, educational technology, educational evaluation, interdisciplinary undergraduate research, health education, business, and entrepreneurship, including journals indexed in Web of Science (ESCI), Scopus (Q1–Q3), ERIC, and DOAJ.

This study examined the association between invitation message tone and student participation in digitally mediated learning environments. Using a field-based quasi-experimental design, 40 students in the Philippines were assigned through an alternating allocation procedure to receive either a formal, context-rich invitation or a brief informal message directing them to the same online task. Participation was measured at the individual level through link activation, task completion, and response timing using automated digital tracking. Results showed higher completion rates and faster response patterns in the formal message condition. Completion reached 100% in the formal condition compared to 50% in the informal condition (χ²(1, N = 40) = 13.33, p < .001, V = .58). These findings show that message structure is associated with how learners respond to academic requests in digitally mediated environments. While limited by a small sample size and context-specific design, the study provides applied evidence consistent with principles of transactional distance and teaching presence. The findings suggest that low-effort improvements in communication design may support participation in asynchronous open and distance learning systems.

This study aimed to address the communication needs of Spanish speakers with aphasia by helping them learn scripted sentences using open-source software. The core of learning scripted sentences is to support people with aphasia to learn daily-life sentences to participate in their communities. This study had two specific aims.

First, to develop a scripted sentence treatment repository in collaboration with stakeholders through an iterative design process. Scripted sentences were designed with and for Spanish speakers with aphasia to ensure that treatment resources were linguistically and culturally appropriate.

Second, to examine the acceptability, usability, and preliminary efficacy of scripted sentence training delivered via open-source software. Participants completed baseline, treatment, and follow-up phases (~13 sessions each), learning a set of sentences (~45 each) from the repository in a single-subject multiple baseline design. Participants and their care partners were interviewed regarding their perceptions of acceptability, usability, and preliminary efficacy. Participants also completed the Client Satisfaction Questionnaire-8 and the System Usability Scale.

The way doctors communicate with patients during office visits can affect the quality of care. Studying conversations between doctors and patients can help doctors improve their communication skills.

To study conversations, researchers rely on written records, or transcripts, of office visits. They read the transcripts and give each conversation topic a label. For example, topics may include smoking or pain. But labeling topics in this way may take a lot of time.

In this project, the research team created and tested a new method to make this work easier using natural language processing, or NLP. With NLP, computer programs interpret written language. NLP methods use a process called machine learning, where computer programs use data to learn how to perform different tasks with little or no human input.

The Higher Education Randomized Controlled Trial (THE-RCT) study aims to capitalize on existing data from postsecondary education RCTs to foster substantive and methodological scholarship and encourage teaching and learning opportunities. The cornerstone of THE-RCT is a restricted access file (RAF). The initial version contains individual-participant data from more than 25 of MDRC's higher education RCTs covering 50 institutions and over 50,000 students. The data were originally collected as part of different randomized controlled trial evaluations of a variety of higher education interventions. The data were collected for different student samples, at different times, and in different locations for each study.

The data were collected from four data sources: 1. Baseline: Baseline student demographic data (e.g., gender, race/ethnicity, age, etc.) were gathered, either via a survey administered to students upon joining the study (but prior to random assignment) or from study colleges' administrative records; 2. College Transcript: Student transcript data (e.g., enrollment, credits attempted, credits earned, GPA) were provided by the study colleges or state higher education agencies; 3. College Credential Attainment: Student credential attainment data were provided by the study colleges or state higher education agencies; 4. National Student Clearinghouse: Student enrollment and credential attainment data were provided by the National Student Clearinghouse via their StudentTracker database. This includes enrollment and credential attainment data at colleges beyond the colleges where the study took place.

The RAF contains student-level data, including baseline demographics (e.g., gender, race/ethnicity), outcomes (e.g., enrollment, credits earned, credentials), an indicator of experimental group (e.g., program or control group), and study variables (e.g., a variable that allows users to link to the RCT-level database).

The Expanding Children's Early Learning (ExCEL) Quality Study: Improving Preschool and Early Care and Education (ECE) Instruction through Curricula, Coaching, and Training was funded by Arnold Ventures and conducted by MDRC and its subcontractors, MEF Associates and RTI International. The study consisted of two phases: ExCEL Quality (EQ; 2019-2020) and ExCEL Quality Continuation (EQC; 2020-2021). This collection contains analysis datasets with calculated measures at the child (DS2) and classroom (DS3) levels, a samples dataset for each phase (EQ = DS1, EQC = DS20), and raw data organized by study phase and data source.

ExCEL Quality

In the EQ study, the research team conducted an experimental study testing two interventions that consisted of curricular and professional development support and that targeted different dimensions of classroom quality, namely:

• A whole-child intervention that targets structural and interactional aspects of classroom quality, using The Creative Curriculum for Preschool, 6th Edition
• A domain-specific intervention with a specific scope and sequence that targets instructional aspects of classroom quality, using Connect4Learning, 1st Edition

ECE centers were selected across four U.S. localities in Head Start and community-based child care settings and were randomly assigned to one of three research conditions (Creative Curriculum, Connect4Learning, or preschool-as-usual). The project was originally designed to assess the impacts of each of the interventions on the content of instruction, teacher practices, classroom quality, and child outcomes, as well as to collect program implementation data. However, because of the COVID-19 pandemic that began in March of the 2019-2020 school year, adjustments were made to the guiding questions and research aims, data sources, and analysis.

ExCEL Quality Continuation

The EQC Study was a non-experimental study, aiming to understand ECE teachers' and administrators' experiences during the COVID-19 pandemic (2020-2021 school year). The sample was a subset of the centers that participated in EQ in the 2019-2020 school year (n=26), plus five newly recruited centers. EQC provided stress management workshops and curricular support (Creative Curriculum or Connect4Learning) to participating centers regardless of their original research condition in EQ.

The Ithaka S+R Library Survey 2022 examines strategy and leadership issues from the perspective of library deans and directors at not-for-profit four-year academic institutions across the United States. Respondents were asked about their strategies related to services, collections, diversity, equity, inclusion, and accessibility (DEIA), budget, and personnel, their leadership roles within and outside of the library, and their vision for the role of the library. Demographic variables include respondents' number of years in their position, respondents' age, race/ethnicity, and Carnegie Classification.

Tools for Life: Relationship-Building Solutions (TFL) is a program designed to improve school climate and safety through the proactive development of elementary and middle school students' interpersonal skills (relationship-building and communication) and intrapersonal skills (self-regulation and resiliency). In the 2016-2017 and 2017-2018 school years, the Jackson (Mississippi) Public School District (JPSD) implemented TFL in grades 1 through 8. RAND researchers conducted a randomized controlled trial to determine whether TFL, integrated into existing school practices, positively affected school climate and safety in the district.

This project described the implementation of TFL in JPSD, calculated its costs, and evaluated the program's effectiveness. TFL was designed to improve whole-school change in relationships among staff and students, but the project researchers found that implementation of TFL in JPSD schools was generally shallow, and the program was rarely, if at all, implemented across a whole school as it was designed. TFL had little impact: After one year of implementation, there were no practically or statistically significant differences between schools that implemented TFL and those that did not in measures of students' social and emotional, school climate, behavioral, or achievement outcomes. In addition to the uneven implementation of the program, methodological limitations of the study and contextual factors in JPSD may have contributed to these finding.

The goal of the Inference-Making and Reasoning in Biology (IMRB) measure was two-fold:

1. To develop a measure that is reliable, valid, and fair across male/female, Under-Represented Minority (URM)/non-URM, and first-generation college/not first-generation students.
2. To document that the measure can predict undergraduate introductory biology course grades

Two different 15-item, 1-hour forms were developed. Examinees (4-year college students planning to take or already taking introductory biology) do not need any specific preparation or knowledge before taking the assessment, as they are given all the information they need to reason with and are asked to draw valid conclusions with that information. These forms can be used in any order and may be administered by any research or course staff. They can be given on paper or on computer, to individuals or groups, once or twice per semester.

The National Study of Learning Mindsets (NSLM), also known as Students' Perspectives about the Transition to High School (PATHS), is a longitudinal research study and program evaluation administered by the University of Texas. The purpose of NSLM is to determine if introducing students to a positive growth mindset as they transition to high school will help improve students' academic success during high school and beyond. A growth mindset was defined as a belief amongst students that intelligence can grow and develop, learning is purposeful, hard work can lead to gained skills and accomplished goals, and that these beliefs can maintain motivation in the face of obstacles.

The sample consisted of more than 16,000 9th grade students across 74 high schools in 27 states. Number of courses taken, course level, and GPA before and after high school were measured within English, math, social studies, and science. Numerous demographic variables were collected for students, teachers, and schools. Student demographics included gender, race, and age. Teacher demographics consisted of race, teaching methods, and educational background. School characteristics such as location, course offerings, and students' average test scores were assessed.

Psychology is one of the most popular undergraduate majors in American universities, despite the fact that the discipline still has many unsettled questions regarding fundamental philosophical and methodological issues. These issues may be associated with a lack of clarity regarding an accurate conception of science and the nature of the relationship between psychology and science with respect to these controversies. Kuhn (1967) has suggested that scientific paradigms are transmitted in textbooks.

To understand how the scientific status of psychology is depicted, 30 undergraduate textbooks were examined. Textbooks were examined on the following categories:

1. What constitutes science is controversial
2. Bad (Pseudo) science
3. Second demarcation problem
4. Deductive stance
5. Inductive stance
6. Verisimilitude/tentativeness of science
7. Theory ladenness of facts
8. The role of theory in hypothesis formation
9. The role of competing theories (i.e. Laudan)
10. Social constructionism (vs. natural kinds)
11. Rhetorical views of science
12. Science and biases (e.g., political influences)
13. The role of ad hoc hypotheses
14. Evolutionary epistemology
15. Recognition of conceptual problems (i.e. is it important for science to address conceptual problems or only empirical ones?)
16. Kuhnian paradigms
17. Mature vs pre-paradigm sciences
18. Strict method vs "anything goes" (i.e. Feyerabend).

Introductory, cognitive, social, and abnormal textbooks were examined.

The ELMC Study collected data to describe the objectives, activities, approaches, strategies, and other aspects of the Early Learning Mentor Coach (ELMC) initiative from the perspectives of Head Start grantees, coaches, and staff. In October 2010, the funds to support the ELMC initiative were distributed to 130 Head Start grantees in 42 states and the District of Columbia for a seventeen month period. Grantees used the funds to hire coaches to provide on-the-job guidance, training, mentoring and technical assistance to Head Start staff. The grant recipients reflected the diversity of Head Start programs, including Migrant and Seasonal Head Start and American Indian and Alaskan Native Head Start grantees. Data was collected using a mixed-methods design (qualitative and quantitative) and the following data collection instruments: a grantee census survey; a coach census survey; coach telephone interviews; and staff telephone interviews with staff who received coaching. At this time, only the quantitative data are available via ICPSR.

Low-income preschool children experience greater risks to their social and emotional development than their more affluent peers. These gaps are observed before children begin their formal schooling, and they remain or increase during the elementary school years. Since social and emotional risks may compromise children's future mental health and peer relationships, addressing them is important in its own right. In addition, social-emotional competence may aid learning: children who have difficulty regulating their emotions and behaviors have been found to receive less instruction, to be less engaged in and less positive about their role as learners, and to have fewer opportunities for learning from peers.

The Head Start CARES (Classroom-based Approaches and Resources for Emotion and Social skill promotion) demonstration tests three distinct approaches to enhancing children's social-emotional development on a large scale within the Head Start system - the largest federally funded early-childhood education program in the United States. Conceived and sponsored by the Office of Head Start and the Office of Planning, Research and Evaluation in the Administration for Children and Families within the United States Department of Health and Human Services, the Head Start CARES demonstration was conducted by MDRC, a nonprofit, nonpartisan education and social policy research organization, in collaboration with MEF Associates and several academic partners.

The three evidence-based social-emotional interventions selected for the Head Start CARES evaluation included: The Incredible Years Teacher Training Program (IY), Preschool PATHS (PATHS), and a one-year version of Tools of the Mind- Play (Tools). The interventions are referred to as "enhancements" because they enriched and complemented existing practices and curricula used in Head Start classrooms. These enhancements represent three "types" of social-emotional programming. That is, while all three were aimed at children's social-emotional development, they varied in their approach to changing this set of child outcomes by targeting somewhat different teacher practices, because they were built on differing theories about how social and emotional skills develop.

Baseline and Follow-up Class-level Impact Analysis Data Files

Data included in class-level data files were collected from external observers and teachers through two sources: Classroom Observations and Teacher Self-Surveys.

Classroom Observations were conducted by observers blind to treatment status who observed the classrooms participating in the study in four different sessions at Spring Baseline and Pre-K Follow-up. This source includes the Classroom Assessment Scoring System (CLASS) scores and the Adapted Teaching Style Rating Scale (Adapted-TSRS) scores.

Teacher Self-Surveys were collected from lead teachers at Spring Baseline and Pre-K Follow-up. This data source includes information on classroom composition as well as teacher demographics, teaching experience, level of stress and depression, and professional relationship with peers and supervisors.

Child-level Impact Analysis Data File

Data included in this file were collected at Fall Baseline, Pre-K Follow-up and K Follow-up from teachers, children and their parents through three sources: Teacher Reports on Individual Children, Direct Child Assessments and Parent Surveys.

Teacher Reports on Individual Children (Teacher Reports) were collected at Fall Baseline, Pre-K Follow-up and K Follow-up. Lead teachers filled out surveys for each child separately, including questions about the child's social skills and behavior, the child's specific knowledge and skills, and the teacher's relationship with the child. Teacher reports were collected for both 4-year-olds and 3-year-olds at Fall Baseline and Pre-K Follow-up, but were not collected for 3-year-olds at K Follow-up. As a cover page to the Teacher Report, a shortened version of the Teacher Self-Survey was collected at K Follow-up and those data are included in this dataset.

Direct Child Assessments were conducted at Fall Baseline and Pre-K Follow-up. The dataset comprises data on a set of tasks measuring different skills for each child separately, including social and emotional skills, self-regulation skills and academic skills. Direct Child Assessments were collected for 4-year- olds only.

Parent Surveys were collected at Fall Baseline and K Follow-up. The survey was administered by phone and includes information on family demographics, parent-teacher involvement, parent's perception of school safety, child's social skills and behavior problems, parental level of stress and depression, and household composition and income. Parent Surveys were collected for 4-year-olds only.

Class-level Implementation Analysis Data File

This data file includes data collected from coaches, trainers and teachers on teacher training, classroom-based coaching, and classroom implementation. The data included in this dataset were collected through five separate instruments: (1) Teacher Training Attendance Forms, (2) Coach Weekly Logs, (3) Coach Monthly Fidelity Logs, (4) Trainer Fidelity Logs, and (5) Teacher's View of the Enhancement. Data collected from the first four data sources were collected multiple times during the implementation year while the fifth was collected once at the beginning of the implementation year. The instruments were administered through the Head Start CARES management information system (MIS) with the exception of the Teacher Training Attendance Forms, which were collected on paper. The file also includes some Teacher Self-Survey variables. Data were collected for program group classrooms only.

Coach-level Implementation Analysis Data File

This data file includes data collected from coaches and trainers on classroom-based coaching. The data included in this dataset were collected through five separate instruments: (1) Teacher Training Attendance Forms, (2) Trainer Supervision Logs, (3) Trainer Logs of Coach Quality, (4) Coach Demographics Survey, and (5) Coach End-of-Year Reflections. The instruments were administered through the Head Start CARES management information system (MIS) with the exception of the Teacher Training Attendance Forms, which were collected on paper.

Audiotape Analysis Data File

The audiotape data file includes data created using qualitative information (audiotape transcripts of coach-teacher meetings) that can be used to conduct analyses on one of the two components of the professional development model for the Head Start CARES demonstration: classroom-based coaching.

Child-level Tracking Data File

The child-level tracking data file includes parent-reported data collected in elementary school for children from the Head Start CARES sample. It includes information from parents about children's location and grade, social skills and problem behaviors at home, and receipt of special services.

The Taiwan Education Panel Survey (TEPS) is a national longitudinal project initiated by Academia Sinica and jointly funded by Ministry of Education, the National Science Council, and Academia Sinica. The objective of TEPS is to stimulate more basic research in the fields of education, sociology, economics, and psychology by employing large scale panel data on representative samples of students, and their parents, teachers, and school administrators. In a nutshell, TEPS has five distinguishing features: (1) Theory driven: The focus is on the skills, behavioral, values, and psychological consequences of schooling institutions and family environments of students. Factors that are found in the literature to affect students' learning outcomes are all included. Specifically speaking, an AOE model of learning outcomes, representing learning capabilities (Ability), learning opportunities (Opportunity), and the amount of effort made by the students (Effort), serves as a guiding framework for questionnaire development. Ability and effort are more on students themselves while opportunities covers family, teachers, and school environment, peers, and so forth.

(2) Student centered and multidimensional and multi-levels: Central to the project were questionnaire surveys of students. The data collection extends to cover the most influential actors in their learning environment: parents, teachers, and schools. It covered nested multiple levels of data - individual students, classes, and schools, etc.

(3) Panel surveys covering multiple programs and multiple cohorts: Students in junior high (G7 to G9), senior high (G10 to G12), vocational (G10 to G12), and junior college (G10 to G14) programs were administered for data collection. All students were followed at least twice. A portion of them were followed four times at G7, G9, G11, and G12. In light of the ongoing transformation of the Taiwanese educational system in 1990s, the project started with two cohorts of approximately 40,000 students, making it possible to employ a quasi-experimental design in future analysis.

(4) National representative samples of the students: Students under data collection were representative samples of the 1984/85 and 1988/89 birth cohorts. Weighting is provided according to the probabilistic sampling design.

(5) Public goods: Data are made available to the public as soon as the data collection and data cleaning is completed, thereby providing an important resource for both academic and policy research.