Student Assessment Research Articles

Swedish L2 teacher cognitions of the initial assessment of students' L1 literacy resources

In this paper, we explore second language (L2) teachers’ cognitions regarding the initial assessment of adult learner literacy in their strongest language. Instruction can thus be adapted according to what is stipulated in the curriculum and syllabus. The literacy assessment is conducted in the student’s strongest language with assistance from an interpreter, translated decoding and reading comprehension tasks and concerns assessment of learners with little or no prior education. Questionnaires and interviews with L2 teachers reveal great variation based on four categories of teacher knowledge, namely, Subject matter knowledge, Knowledge of students, Pedagogical knowledge, and Knowledge of educational contexts. These four categories were partly intertwined with each other and both a resource and a deficit perspective emerged. The teachers’ cognitions regarding the concept of literacy, the value of initial L1 literacy assessment and students’ prior literacy and multilingual resources, as well as its potential for instruction planning were diverse. This may have significant implications for what emerges in initial assessments of a student's L1 literacy. In turn, this affects the validity of the assessment and, ultimately, the quality of education.

Does private education pay off?

AbstractEducation plays a crucial role in promoting innovation, entrepreneurship, and equal opportunities in society, acting as a “social elevator.” However, an inequitable educational system can perpetuate inequalities, leading to significant social consequences. This paper examines two mechanisms through which schooling systems may generate or reinforce inequalities: private schooling and school composition. Earlier studies often suggested that private schooling, particularly government-dependent private schools, had a positive impact on student achievement. However, more recent research has challenged this view, highlighting the importance of contextual factors such as school composition and socio-economic background. Building on these findings, our analysis explores how the advantages attributed to private schools are shaped by the demographic profiles of their students. Using data from the OECD Program for International Student Assessment (PISA) 2015 and employing an education production function, we assess the effects of private schooling and school composition on student performance. Our findings contribute to the growing body of research questioning the comparative advantage of private schools, demonstrating that their perceived superiority often arises from the socio-economic advantages of the students they enroll, rather than the quality of education provided. The study also reveals significant variations across countries, underscoring the urgent need to address the segregation issues linked to private school networks.

Exploring How Education Can Leverage Artificial Intelligence for Social Good

Artificial intelligence (AI) is rapidly transforming society and industries, presenting both opportunities and ethical challenges. AI enables machines to perform tasks traditionally done by humans, such as natural language processing, pattern recognition, decision-making, and problem-solving (Brookings, 2023). In education, AI enhances teaching methodologies, student assessment, and administrative tasks through tools like intelligent tutoring systems, adaptive learning platforms, and educational chatbots. These tools offer customised learning experiences, immediate feedback, and data-driven insights. This research aims to investigate how AI can be leveraged within education to promote social good by identifying how familiar educators and students are with AI tools, identify how educators and students perceive the role of AI in education and what are the current applications of AI technologies in educational settings and how widely are they used. Finally, discuss the opportunities and ethical considerations of integrating AI in education. AI technologies can address critical social challenges such as inequality, accessibility, and personalised learning. According to Luckin et al. (2016), "AI can provide tailored educational experiences that adapt to individual learning needs, thus promoting equity in education." This exploratory research begins with an overview of AI's role and tools in education, followed by a discussion of the challenges, opportunities, and ethical considerations associated with AI integration. Understandings are drawn from educator’s response to a questionnaire and a focus group with first year and final-year third level students. This qualitative data, analysed using NVivo software, reveals key themes and significant findings on effectively utilising AI in education.

Performance of large language artificial intelligence models on solving restorative dentistry and endodontics student assessments

ObjectivesThe advent of artificial intelligence (AI) and large language model (LLM)-based AI applications (LLMAs) has tremendous implications for our society. This study analyzed the performance of LLMAs on solving restorative dentistry and endodontics (RDE) student assessment questions.Materials and methods151 questions from a RDE question pool were prepared for prompting using LLMAs from OpenAI (ChatGPT-3.5,-4.0 and -4.0o) and Google (Gemini 1.0). Multiple-choice questions were sorted into four question subcategories, entered into LLMAs and answers recorded for analysis. P-value and chi-square statistical analyses were performed using Python 3.9.16.ResultsThe total answer accuracy of ChatGPT-4.0o was the highest, followed by ChatGPT-4.0, Gemini 1.0 and ChatGPT-3.5 (72%, 62%, 44% and 25%, respectively) with significant differences between all LLMAs except GPT-4.0 models. The performance on subcategories direct restorations and caries was the highest, followed by indirect restorations and endodontics.ConclusionsOverall, there are large performance differences among LLMAs. Only the ChatGPT-4 models achieved a success ratio that could be used with caution to support the dental academic curriculum.Clinical relevanceWhile LLMAs could support clinicians to answer dental field-related questions, this capacity depends strongly on the employed model. The most performant model ChatGPT-4.0o achieved acceptable accuracy rates in some subject sub-categories analyzed.

University Teachers’ Views on the Adoption and Integration of Generative AI Tools for Student Assessment in Higher Education

This study examines the factors that may impact the adoption of generative artificial intelligence (Gen AI) tools for students’ assessment in tertiary education from the perspective of early-adopter instructors in the Middle East. It utilized a self-administered online survey and the Unified Theory of Acceptance and Use of Technology (UTAUT) model to collect data from 358 faculty members from different countries in the Middle East. The Smart PLS software 4 was used to analyze the data. The findings of this study revealed that educators developed new strategies to integrate Gen AI into assessment and used a systematic approach to develop assignments. Moreover, the study demonstrated the importance of developing institutional policies for the integration of Gen AI in education, as a driver factor influencing the use of Gen AI in assessments. Additionally, the research identified significant factors, namely performance expectancy, effort expectancy, social influences, and hedonic motivation, shaping educators’ behavioral intentions and actual use of Gen AI tools to assess students’ performance. The findings reveal both the potential advantages of Gen AI, namely enhanced student engagement and reduced instructor workloads, and challenges, including concerns over academic integrity and the possible negative impact on students’ writing and thinking skills. This study emphasizes the significance of targeted professional development and ethical criteria for the proper integration of Gen AI in educational assessment.

Cultural capital, black holes, and the hidden curriculum: an analysis of grade repetition in Spain

ABSTRACT In this article I explain the contradiction between the averagely high and equitable scores that Spanish students obtained in the last three editions (2015, 2018, and 2022) of the Program for International Student Assessment, and Spain’s extremely high and unequitable rate of grade repetition in schools. After ruling out alternative explanations for this discrepancy, I explore the hypothesis that grade repetition in Spain is an effect of the hidden curriculum. Methodologically speaking, my explanation establishes analogies with Einstein’s theory of relativity and draws on its spatial topoi to conceptualize the difference between the official and the hidden curriculum and the undemocratic conflation between upper- and middle-class cultural capital and academic skills. This conflation, I argue, lies behind said contradiction between Spanish students’ scores in PISA and the rates of grade repetition in Spain.

Teaching social work students about evidence-based practice using peer-led learning and assessed conversations

ABSTRACT While the assessment of students on social work placement has attracted a sizable body of research and commentary, on-campus assessments have attracted less attention. With advances in artificial intelligence and the rise of essay-mills, the rigor of assessment by assignment submission is threatened. Acknowledging the need for educators to review assessment in-line with these contemporary challenges and importance of developing skills for practice, this paper presents an evaluation of implementing assessed conversations in a compulsory evidence-based practice module for Bachelor of Social Work students. Replacing group presentations, students agreed with the introduction of assessed conversations to foster authentic collaboration with peers; while assuring students they would receive formative feedback on their performance before being formally assessed. Sixty students took part in nine focus groups offering feedback on their experience of assessed conversations. Students suggested this was a more challenging form of assessment, however, growth and development was reported. Students described a depth of knowledge achieved and greater confidence in evidence-based practice then they had envisaged possible. Findings suggested three possible factors in successfully implementing assessed conversations: Extensive peer support, formative assessed conversations, and learning by doing. Options for the continuation of research on assessed conversations are discussed.

Enhancing Integration of Technology in Authentic Assessment for Education: A Structured Review

In the ever-evolving landscape of education, the seamless integration of technology into authentic assessment practices has become a transformative force, reshaping how students are both evaluated and engaged. Authentic assessment, characterized by its emphasis on the real-world application of knowledge and skills, has gained prominence for its ability to gauge students' comprehension and foster deeper learning experiences. As technology continues to infiltrate the educational field, a pressing need arises to assess the effectiveness of these digital tools in promoting genuine understanding and critical thinking among students. This structured review of the PRISMA approach was applied to find the primary data based on keywords such as Technology, Science, and Authentic Assessment. Based on advanced searching on SCOPUS and Web of Science, we found (n=55). Expert scholar decided to develop 3 themes, which are (1) Online Assessment and Technology- Enhanced Learning, (2) Educational Practices and Student Engagement, and (3) Assessment and Curriculum Development. The findings underscore technology's immense potential in elevating authentic assessments for students, offering new avenues for engagement and skill development. It is evident that when wielded thoughtfully and integrated into pedagogy, technology can empower young learners to explore, inquire, and excel in the fascinating world of education. This study not only bridges existing gaps in the literature but also serves as a valuable resource for educators and policymakers alike, providing insights into harnessing technology's power to enhance authentic assessment practices and, consequently, the overall educational experience.

Predictive Analysis of Students’ Learning Performance Using Machine Learning

Several researchers and educational institutions got attracted to the domain of predicting the performance of the students to classify the educational level of student performance. Though the educational sector uses several techniques for extracting useful information about them and the measures to be undertaken in the learning process, it is necessary to develop a student performance assessment model to assist the students as well as faculty members to improve their performance to the next level. This research work majorly concentrates to examine and identify useful rules and patterns to motivate the students for handling their education as well as career in a better way and also to improve the functioning of academics to supervise the policies for students’ benefit. Here, EDM is employed to identify the effective data which helps in applying the active learning in technical applications. Initially, a review of different DM, machine learning (ML), and meta-heuristic models to assess the performance of the students. the proposed models can be employed as an appropriate tool for mining educational data to achieve effective performance assessment of the students.

Primary school students’ ratings of teaching – do they differentiate between subjects and teachers?

ABSTRACT Our study aims to provide empirical evidence for and against the valid use of primary school students’ ratings of three generic dimensions of teaching quality (classroom management, supportive climate, cognitive activation). We examine whether students discriminate between corresponding dimensions in different subjects, taking into account whether these subjects are taught by the same or different teachers. Using data from the German Trends in International Mathematics and Science Study 2015 assessment of 3,853 fourth graders (M age = 8.8 years, 195 classes), we conduct multilevel-multigroup confirmatory factor analysis. The results suggest that students only differentiate between subjects when taught by different teachers. The findings also imply that valid inferences from student assessments may be affected by students’ experiences with multiple teachers.

Assessment of female students' perception on access and utilization of water and sanitation facilities for menstruation management in higher education institutions in Uganda

AbstractThe main purpose of this study was to assess female students' perception of access and utilization of water and sanitation facilities for menstruation management in HEIs. A qualitative research design was embraced, and it was exploratory while gathering responses from the participating respondents using semi‐structured interviews, focus group discussions and observation from course coordinators from six faculties, students guild leadership, and selected university managers who were purposively selected and regarded to be more knowledgeable with university affairs as far as learners' social welfare was concerned. The study found that many students did not have adequate access to water and sanitation facilities for menstruation management. They also lack adequate menstrual hygiene management education and their rights to sanitation and water facilities for menstruation management in terms of the menstrual cycle, the importance of washing body parts, and the issue of stigma during the menstruation period. The study recommended that the Directorate of Gender at the university should review and work very closely with the Department of Estates and Works to improve the maintenance and provision of water and sanitation facilities for menstruation management.

Engaging Environmental Education Through PISA: Leveraging Curriculum as a Political Process

Abstract The Organisation for Economic and Cultural Development (OECD) works with countries worldwide to implement testing in the areas of science, mathematics and reading through the Programme for International Student Assessment (PISA) every three years, and this process is recognised to influence education systems through areas such as curriculum. Over the past decade, the OECD increasingly has acknowledged the need to include a greater emphasis on environmental issues, including developing student competencies specifically in this area. For the 2025 PISA round, we were invited as environmental science education experts to contribute to the Science Framework, which underpins the science assessment. This paper explains how we responded to that invitation, including foregrounding the urgent need to understand the competencies of 15 year-olds to address critical socio-ecological challenges such as climate change. We argue that this provides environmental education practitioners and scholars with a powerful opportunity to gain world-scale data for research and advocacy, which could enhance the visibility and leverage for our field in curriculum, whilst also recognising the political process within which we were engaged.

Psychology Students’ Experiences of the Objective Structured Clinical Examination as an Assessment of Professional Skills in Psychology

A challenge for professional psychology programs is the assessment of students’ professional competence. Despite its potential, objective structured clinical examination (OSCE) has not gained widespread use in the psychological field. However, at Umeå University and Örebro University in Sweden, the OSCE has been introduced at the Clinical psychology programs to assess professional competence. The aim of this study was to explore students’ perceptions of whether and how, preparing for and performing the OSCE benefits their professional learning and prepares them for clinical practice. A web-based questionnaire was administered to 88 psychology students who completed the OSCE and field training. Most of the students perceived the OSCE as a valuable experience that benefits their learning. The OSCE prepared them for clinical practice through practical hands-on training, and by providing essential experience in client interaction, increasing students’ confidence in the role as a psychologist. Students also reported that feedback from the OSCE was crucial for their ongoing learning, but that the authenticity of the examination can be improved. Based on these findings, recommendations for future OSCEs in professional psychology include appropriate preparations, providing constructive feedback as well as striving for high authenticity in the tasks of the OSCE stations.

Web-Based System Enhances Extracurricular Management Efficiency in Educational Institutions

Background: The advancement of information technology has significantly influenced educational management, particularly in managing extracurricular activities within schools. Specific Background: Traditional methods of managing these activities often lead to time-consuming processes and ineffective communication, highlighting the need for a more efficient system. Knowledge Gap: While various management systems exist, few specifically address the challenges faced in managing extracurricular activities effectively and transparently. Aims: This research aims to develop and implement a web-based Extracurricular Management Information System (SIMAK) to enhance efficiency and transparency in managing extracurricular activities. Results: Utilizing Agile methodology with the Scrum model and the Laravel framework, the study successfully developed the SIMAK application, which supports activity registration, schedule management, attendance tracking, and student assessments. The implementation of SIMAK resulted in improved administrative efficiency, streamlined processes, and increased transparency in information access for administrators, coaches, and students. Novelty: This study presents a unique approach to extracurricular management by leveraging modern technology and methodologies to address existing inefficiencies in educational settings. Implications: The findings suggest that the SIMAK application not only enhances the management of extracurricular activities but also encourages greater student participation and provides schools with better data for decision-making. Overall, the application significantly contributes to optimizing students' educational experiences outside the classroom, promoting a more organized and transparent approach to extracurricular management. Highlights: Efficiency: Streamlines registration and scheduling processes for extracurricular activities. Transparency: Improves information access for all users involved. Engagement: Increases student participation in extracurricular activities. Keywords: Extracurricular Management, Information System, Agile Methodology, Transparency, Education Technology

Research on Mental Health Assessment and Intervention Methods for College Students based on Big Data Analysis

This study introduces the novel Fuzzy-Enhanced Predictive Neural System for Student Mental Health (FEPS-MH) approach to mental health assessment and intervention for college students. FEPS-MH synergistically combines a Backpropagation (BP) Neural Network with a Deep Fuzzy-Based Neural Network (DFBNN), leveraging the strengths of both systems to handle the complexities of mental health data in the context of big data analytics. The BP Neural Network, known for its effective learning and generalization capabilities, is integrated with the DFBNN to process imprecise, uncertain, or subjective data, typical in mental health assessments. The core objective of FEPS-MH is to provide a more accurate, robust, and sensitive analysis of mental health states, incorporating the nuanced variations and uncertainties inherent in psychological data. This system is designed to analyze a vast array of data sources, including but not limited to, behavioral patterns, self-reported questionnaires, and social media interactions, to identify potential mental health issues among college students. FEPS-MH’s capabilities extend beyond mere assessment; it is also equipped to recommend personalized intervention strategies. Utilizing big data analysis, the system not only predicts potential mental health crises but also suggests tailored intervention approaches based on the unique psychological profile of each student. This study demonstrates the feasibility and effectiveness of FEPS-MH through a series of tests and validations using real-world data. The results indicate a significant improvement in both the accuracy of mental health assessments and the efficacy of suggested interventions. FEPS-MH stands as a promising tool for educational institutions, offering a data-driven, sensitive, and comprehensive approach to student mental health care. Its implementation could revolutionize the field of mental health support in college environments, making it a vital asset for proactive psychological wellness in educational settings.

Description of a Longitudinal Interprofessional Education Plan and Outcomes From an Inaugural Student Cohort

ObjectiveTo describe a longitudinal interprofessional education (IPE) plan at 1 school of pharmacy including inaugural student cohort outcomes. MethodsStandards 2016 prompted the creation of an IPE task force at the University of Wisconsin–Madison School of Pharmacy to develop and implement an IPE plan consisting of outcome-based goals, a deliberate design, and a formalized assessment strategy (an approach that inspired national consensus guidance from the Health Professions Accreditors Collaborative). Beginning with the 2022 graduating class, required interprofessional learning activities were embedded longitudinally across a 4-year Doctor of Pharmacy program and included classroom-, simulation-, and clinical-based IPE activities. Student learning outcomes, focused on attitudes, skills, and behaviors, were assessed longitudinally using 3 self-reported, validated measures allowing before and after comparisons: Student Perceptions of Interprofessional Clinical Education–Revised, Version 2, Interprofessional Education Collaborative Competency Self-Assessment Tool, Version 3, and Interprofessional Collaborative Competencies Attainment Survey–Revised, coupled with the Individual Teamwork Observation and Feedback Tool. ResultsEnd point Student Perceptions of Interprofessional Clinical Education–Revised, Version 2 and Interprofessional Education Collaborative Competency Self-Assessment Tool, Version 3 average scores were in the agree to strongly agree range with statistically significant before and after change in 80% (4 of 5) of subscales. Students’ attainment and demonstration of positive teamwork behaviors were evidenced by statistically significant before and after changes in advanced pharmacy practice experience student Interprofessional Collaborative Competencies Attainment Survey–Revised scores and universal satisfactory ratings of advanced pharmacy practice experience students on the Individual Teamwork Observation and Feedback Tool. ConclusionA developmentally progressive, longitudinal IPE plan was implemented into a 4-year Doctor of Pharmacy program. Inaugural student cohort assessment results documented students were prepared for interprofessional practice upon graduation.

Enhancing digital literacy skills among teachers for effective integration of computer science and design education: a case study at Astana International School, Kazakhstan

This study explores the development and impact of digital literacy skills among teachers at Astana International School, Kazakhstan, and examines how these skills influence the teaching of Computer Science and Design to middle school students. Employing a mixed-methods approach, the research combined quantitative assessments of students’ proficiency with qualitative evaluations of teacher and student experiences, involving 71 teachers and 382 students from grades 7 to 10. The findings indicate that students taught by digitally literate teachers demonstrated significant improvements in designing and utilizing virtual reality tools, mobile applications, and other digital resources, with teachers facilitating more interactive and engaging learning environments that enhanced students’ technical skills and creative capacities. This research contributes new insights into the dynamics of digital literacy in education, emphasizing the critical role of teacher training in digital tools for enhancing educational practices and uniquely demonstrating how systematic application of digital literacy can transform educational outcomes, supporting the integration of technology in teaching, aligned with the needs and competencies of Generation Z students.

An adaptation of Random Forest to estimate convex non‐parametric production technologies: an empirical illustration of efficiency measurement in education

AbstractThis paper presents a novel approach to conduct non‐parametric estimations of production technologies that adhere to the basic assumptions of production theory axioms, including free disposability in inputs and outputs and convexity. The methodology is rooted in adapting the highly effective machine learning techniques associated with Random Forest and the use of splines. The new method features a piecewise linear estimator analogous to data envelopment analysis (DEA); however, it distinguishes itself by addressing DEA's overfitting and lack of robustness via randomization of data and input variables in the construction of the models. In this paper, the virtues of employing machine learning techniques for assessing the efficiency of public services, particularly in the realm of educational institutions, are underscored. The new approach has the capability to predict outputs based on inputs, even for units not included in the observed sample. Furthermore, it enables the identification of the most relevant inputs in relation to output production. To demonstrate the advantages of our method, an estimation of the educational production function is conducted for Spanish regions utilizing data sourced from the Program for International Student Assessment.

396 Behavior Cuing in Student Assessments Improves Feedback Concordance

396 Behavior Cuing in Student Assessments Improves Feedback Concordance

The influence of ICT competencies on English digital reading achievement

Due to the prevalence of information and communication technologies (ICT) among secondary school students and the increasing significance of digital reading, exploring the impact of ICT on students’ digital reading performance in English seems necessary. The current research aimed to examine the effects of ICT competencies factors on secondary school students’ English digital reading performance. Data were obtained from 7703 15-year-old students from three East Asian economies, Macau, Hong Kong, and Singapore, from the Programme for International Student Assessment (PISA) 2018 dataset. The results of hierarchical regression analysis revealed that students’ ICT literacy was negatively correlated with their English digital reading performance, while the influence of attitudes toward ICT varied across the three East Asia economies. Additionally, males had lower English digital reading achievement, while students with higher socioeconomic status (SES) had higher English digital reading performance.