assessment-literacy
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- PaperDOAJ — Language assessment1 Jul 2026
The Design of Language Testing and Evaluation Materials for the English Department
Irra Wahidiyati, Windhariyati Dyah K, Ghaida Thifal
A needs analysis of English department students and lecturers informed the design of a 10-chapter textbook on language testing and evaluation. The material covers assessment concepts, principles, and specific techniques for listening, speaking, reading, writing, grammar, and vocabulary. The resulting resource aims to improve Language Assessment Literacy by integrating theory, test construction, and rubric development.
Original abstract
Background - The students of Tadris Bahasa Inggris need explicit material about assessments and tests. They need the material to develop listening and speaking skills. Next, the TBI students must master the creation of writing and reading test items. In addition to creating writing and reading test items. Urgency of Research – The needs analysis shows that students’ needs regarding the Language Testing and Evaluation subjects in the English Department of UIN Prof. K. H. Saifuddin Zuhri Purwokerto. They need information on how to create assessment rubrics for them. The learning materials used are compiled to meet the students' needs. Research Objectives – This study conducts a needs analysis of students' needs regarding the Language Testing and Evaluation subject and designs new material for it. Research Method - A mixed method was used to answer the research questions. The researcher analyzed the institution's problems and assessed whether students' needs aligned with the syllabus or lesson plan. The information sources were 100 students and 2 lecturers. Research Findings – The draft of the material consists of 7 chapters. Chapter 1 discusses assessment concepts and issues. Chapter 2 discusses the principles of language assessment. Chapter 3 discusses the design of classroom language tests and standardized testing. Chapter 5 discussed the assessment of listening, including intensive, responsive, selective, and extensive listening. Chapter 6 discusses assessing speaking, including imitative, intensive, responsive, interactive, and extensive speaking. Chapter 7 discusses the assessment of reading, including perceptive, selective, interactive, and extensive reading. Chapter 8 discusses assessing writing, including imitative, intensive, responsive, and extensive. Chapter 9 discusses the assessment of grammar and vocabulary. The last chapter discusses the grading and evaluation process. Research Conclusion & Novelty - The materials integrate assessment theory, test construction, and rubric development for all language skills into a single contextualized resource designed to promote Language Assessment Literacy.
- PaperAssessment & Evaluation in Higher Education1 Jul 2026
Which grades predict what? A more nuanced understanding of using high school results for university admission
Sebastiaan Steenman, Ada Kool
Overall high school GPA consistently outperforms subject-specific grades in predicting university performance, but taking related subjects shows small positive effects. Predictive validity decreases over time and is stronger for lower-order cognitive skills.
Original abstract
While high school grades are widely used for university admissions, little is known about which specific high school grades best predict what type of performance at university. This study examines the predictive value of overall high school GPA (grade point average), grades for subsets of subjects, and the added value of having taken specific subjects, for university performance across different cognitive learning objectives, different programmes and over time. Using data from multiple cohorts of six undergraduate programmes at a large Dutch research university, we show that the overall high school GPA consistently outperforms subsets of discipline-related subjects, suggesting that high school grades primarily represent general learning skills and traits. However, having taken a specific related high school subject was generally associated with better university performance, although effect sizes were small. High school grades predicted performance better on assessments targeting lower-order cognitive skills than complex academic tasks. No significant differences emerged between the predictive value of high school final-year and penultimate-year grades. Finally, the predictive strength declined over the course of the three-year bachelor programmes. These findings highlight the need for careful consideration of which high school grades to use in admissions and provide practical suggestions for university admissions officers to do so.
- PaperAssessment & Evaluation in Higher Education4 Jun 2026
University instructors’ contemporary assessment literacy: development and validation of a questionnaire
Goudarz Alibakhshi
The study developed and validated a 35-item questionnaire measuring university instructors' contemporary assessment literacy across nine dimensions, including learning-oriented assessment, feedback, learner involvement, ethics, digital and AI-responsive assessment, inclusivity, consequential validity, and learning analytics. The instrument was refined through expert review and administered to 462 Iranian instructors, with factor analysis supporting the multidimensional structure. This tool addresses gaps in existing measures by capturing modern assessment demands such as AI and learning analytics.
Original abstract
Assessment literacy has become a key professional competence in higher education, where instructors are expected to design learning-oriented, ethical, inclusive, digitally mediated and evidence-informed assessment practices. However, existing measures do not fully capture contemporary demands related to feedback, learner involvement, artificial intelligence, learning analytics, accessibility and assessment consequences. This study developed and validated a questionnaire measuring university instructors’ contemporary assessment literacy. Using a multiphase, mixed-methods instrument development design, the study was conducted in two sequential phases. In Phase 1, a preliminary 39-item pool was reviewed by 22 assessment experts from three universities in Tehran. Expert ratings supported item relevance, clarity, representativeness and essentiality, and 12 items were revised. In Phase 2, the revised questionnaire was administered to 670 university instructors from four Tehran universities; 462 usable responses were returned. Exploratory factor analysis supported a nine-factor solution explaining 66.66% of the variance. The retained dimensions were learning-oriented assessment literacy, feedback literacy, learner involvement, fairness and ethics, digital assessment literacy, AI-responsive assessment literacy, inclusive and accessible assessment literacy, consequential validity and washback literacy, and assessment data and learning analytics literacy. Confirmatory factor analysis supported the final 35-item model, with satisfactory reliability, convergent validity, discriminant validity and model fit.