Learning and Individual Differences最新文献

{"title":"Individual differences in language learning and teaching: Growing pains at the theory-methods interface","authors":"Yasser Teimouri ,&nbsp;Ekaterina Sudina ,&nbsp;Luke Plonsky","doi":"10.1016/j.lindif.2025.102786","DOIUrl":"10.1016/j.lindif.2025.102786","url":null,"abstract":"<div><div>The role of individual differences (IDs) in second language acquisition (SLA) is well established, with two dedicated journals, a biannual conference, book series, handbooks, and a professional organization all focused on this area. However, these structural and visible signs of growth may present an overly optimistic view of the domain's maturity. As we argue in this paper, a closer look at IDs in SLA reveals significant concerns in theory, methods, and their interface, with construct validity emerging as a critical issue. Despite a large body of empirical research, relatively few IDs have been sufficiently theorized or rigorously validated, leading to exploratory analyses, susceptibility to HARKing, and other questionable research practices (see Hiver &amp; Al-Hoorie, 2020; Isbell et al., 2022). Methodologically, while recent efforts at scale validation (e.g., Botes et al., 2021; Teimouri, 2018) are commendable, a lack of systematic validation and insufficient attention to construct clarity undermine the field's theoretical robustness and empirical reliability (Papi &amp; Teimouri, 2024; Sudina, 2021, 2023a). Furthermore, as shown in other domains of SLA (e.g., Plonsky, 2023), research on IDs often overlooks understudied and underserved populations, limiting both its generalizability and social utility. This paper addresses these critical issues and their impact on the field's contributions to theory and practice, offering specific, actionable recommendations to guide future research.</div></div><div><h3><em>Educational relevance</em></h3><div>This study highlights the critical importance of construct validity in Individual Differences (IDs) research within Second Language Acquisition (SLA). We argue that failing to validate constructs rigorously leads to theoretical ambiguities, unreliable findings, and misleading conclusions. In addition, replicating studies without ensuring construct validity risks reinforcing conceptual flaws rather than advancing scientific knowledge. By prioritizing construct validation in SLA, educators, researchers, and policymakers can rely on more accurate assessments of learner differences, leading to better-informed language learning interventions and teaching strategies.</div></div>","PeriodicalId":48336,"journal":{"name":"Learning and Individual Differences","volume":"124 ","pages":"Article 102786"},"PeriodicalIF":9.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145109503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Individual differences in learning from digital texts: What do we know and where do we go from here?","authors":"Kate Cain","doi":"10.1016/j.lindif.2025.102803","DOIUrl":"10.1016/j.lindif.2025.102803","url":null,"abstract":"<div><div>Digital reading has become integral in our education, recreational reading, and professional lives. The papers in this special issue explore individual differences in how readers understand, process, and learn from digital texts across different age groups and tasks. This commentary summarises study findings about the similarities in processing information presented on paper and on screen, and the unique challenges that arise through the content and activities that are a focus of digital reading, such as internet-based search and learning. I conclude with recommendations for future research to elucidate how reader characteristics and experience interact with digital reading tasks and texts to influence comprehension and learning.</div></div>","PeriodicalId":48336,"journal":{"name":"Learning and Individual Differences","volume":"124 ","pages":"Article 102803"},"PeriodicalIF":9.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145107699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigating the influence of data-driven learning (DDL) on EFL students' willingness to attend classes (WTAC): An intervention study","authors":"Yongliang Wang ,&nbsp;Xiaofang Yan","doi":"10.1016/j.lindif.2025.102788","DOIUrl":"10.1016/j.lindif.2025.102788","url":null,"abstract":"<div><div>The nature of data-driven learning (DDL) has made it a prominent topic in L2 research. While previous studies have often examined its impact on linguistic development, relatively few have investigated its effects on learners' individual traits and attitudinal variables. In the present study, willingness to attend classes (WTAC) is conceptualized as an <strong>attitudinal variable</strong> reflecting learners' motivation and inclination to participate in classroom activities. To address this gap, this experimental study evaluated the impact of DDL tasks on English as a foreign language (EFL) learners' WTAC. A total of 147 EFL learners were assigned to a control group (<em>n</em> = 73) receiving traditional instruction and an experimental group (<em>n</em> = 74) engaging in DDL tasks. WTAC was measured using a questionnaire administered at both the beginning and end of the semester. ANCOVA results indicated that incorporating DDL tasks into EFL classrooms significantly enhanced WTAC in the experimental group. These findings suggest that adopting a DDL approach can positively influence learners' classroom engagement by shaping their attitudes toward attendance.</div></div><div><h3>Educational relevance statement</h3><div>Data-driven learning (DDL) includes the use of corpus technology (directly or indirectly) to explore regular and authentic patterns of target language use and develop classroom tasks and activities in light of concordance outputs. Willingness to attend classes (WTAC) concerns learner's tendency and passion to be present in the classes. The current study examines the effect of DDL tasks on the degree of WTAC among Chinese EFL students. The findings of this study show that integrating technologies and corpus linguistic has positive influences on L2 learning and learners' attitudes and dispositions toward education and DDL can permeate into the psycho-affective, attitudinal, and behavioral aspects of L2 education, if it is effectively injected into the classes. The results may be theoretically significant for expanding theories related to DDL, discovery learning, and the noticing hypothesis.</div></div>","PeriodicalId":48336,"journal":{"name":"Learning and Individual Differences","volume":"124 ","pages":"Article 102788"},"PeriodicalIF":9.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145060753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beyond linear regression: Statistically modeling aptitude-treatment interactions and the differential effectiveness of educational interventions","authors":"Peter A. Edelsbrunner ,&nbsp;Leonard Tetzlaff ,&nbsp;Katharina M. Bach ,&nbsp;Denis Dumas ,&nbsp;Sarah I. Hofer ,&nbsp;Carmen Köhler ,&nbsp;Zoya Kozlova ,&nbsp;Julia Moeller ,&nbsp;Frank Reinhold ,&nbsp;Garrett J. Roberts ,&nbsp;Marie-Ann Sengewald ,&nbsp;Sarah Bichler","doi":"10.1016/j.lindif.2025.102812","DOIUrl":"10.1016/j.lindif.2025.102812","url":null,"abstract":"<div><div>Research on aptitude-treatment interactions and the differential effectiveness of educational interventions faces statistical challenges that may contribute to sparse findings and unclear replicability. These challenges include the presence of nonlinear-, floor-, or ceiling effects, underpowered samples, and the multivariate nature of learner aptitudes. Linear regression, which prevails as the typical statistical approach in this research area, lacks the flexibility to meet these challenges. As alternatives, we present three statistical approaches: (1) Additive regression models to capture and control nonlinear or floor/ceiling effects, (2) Bayesian multilevel modeling, which can improve statistical power and allows for more complex models, and (3) clustering multivariate constellations of learner aptitudes via latent profile analysis. We demonstrate these three approaches on a motivating dataset from a scientific reasoning training, discussing their relative (dis-)advantages and how these and further models may aid research into differential effectiveness across different research topics and designs.</div></div><div><h3>Educational relevance statement</h3><div>In educational interventions, researchers and practitioners are often interested in knowing for whom an intervention works best or worst. We present three statistical models that can help examine this question and overcome issues that have long bugged this field. We discuss how these approaches can help research across multiple areas, for example to examine the effects of educational technologies (augmented &amp; virtual reality).</div></div>","PeriodicalId":48336,"journal":{"name":"Learning and Individual Differences","volume":"124 ","pages":"Article 102812"},"PeriodicalIF":9.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145333095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Defining external regulation on standardized test instructions: A key variable for the academic success of students in the digital world","authors":"Shir Bach-Kay ,&nbsp;Maggie E. Toplak","doi":"10.1016/j.lindif.2025.102805","DOIUrl":"10.1016/j.lindif.2025.102805","url":null,"abstract":"<div><div>Determining the degree of external regulation by educators in the increasing digitalization of the school context is one of the most important issues we are facing in the future of students' learning. Educators must determine how to set up the learning environment and amount of direction provided to elicit their student's best performance. Standardized test assessments of cognitive abilities provide an important reference point for operationalizing how degree of examiner structure and direction during the administration of these tests may be related to individual differences in student performance. Our analysis of standardized instructions of several different measures of cognitive assessments illustrates how these assessments vary in their degree of external regulation, such as specifications of set up of physical environment, amount of instruction and feedback provided, examiner direction during administration and timing factors. Based on a coding scheme to identify and quantify these factors, we present a proof of concept by examining whether degree of external regulation may explain individual differences in test performance, particularly in at-risk learners such as child and youth with ADHD. Operationalizing what we have learned from years of refining instructions for standardized test administration can serve as a useful reference point for determining factors to optimize student learning within the digitalization of learning environments.</div></div><div><h3>Educational relevance statement</h3><div>This paper discusses the importance of the environment (more specifically, the testing environment) for students' success, particularly at-risk learners such as students with ADHD. To illustrate how environmental structure can impact student performance, instructions for standardized test assessments of cognitive skills were used to show how environmental structure can be operationalized in learning environments. Standardized test assessments of cognitive abilities provide an important reference point for operationalizing how degree of examiner structure and direction during the administration of these tests is related to individual differences in student performance. In this paper, we surveyed the instructions of some of the most common standardized assessments of cognitive abilities (intelligence and executive function tasks) to operationalize the types and degree of structure provided as part of the instructions and administration of these tests. Then, we identified illustrative studies to demonstrate how the nature and amount of examiner direction may explain individual differences in test performance, particularly in at-risk learners such as students with ADHD. Finally, the relevance for at-risk learners in online learning environments is discussed, given that this environment may be particularly challenging for educators to control and regulate to optimize learners' success.</div></div>","PeriodicalId":48336,"journal":{"name":"Learning and Individual Differences","volume":"124 ","pages":"Article 102805"},"PeriodicalIF":9.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145268315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Digital reading and what makes it hard for whom: Individual differences in learning from digital texts","authors":"Eliane Segers ,&nbsp;Byeong-Young Cho ,&nbsp;Johannes Naumann","doi":"10.1016/j.lindif.2025.102801","DOIUrl":"10.1016/j.lindif.2025.102801","url":null,"abstract":"<div><div>We introduce a special issue on digital reading that focuses on examining the roles and contributions of reader individual differences in learning from digital texts. In this introduction, we explain how reading of digital texts can be viewed from different angles. A first angle is that of the text, which is often the dichotomized between print (e.g., paper) versus digital (e.g., computer screen). Specific elements of digital texts (e.g., interactivity, hypertextuality, multimodality, uncertainty) pose additional questions. Second is the reader, and individual differences among readers. The third angle regards task variables. Together, these three shape the processing of digital texts, which is the fourth angle in reading digital texts. We argue that the science of reading needs to expand to include the science of digital reading, as not all that is known from paper reading can be transferred one-on-one to digital reading. Digital text with all its opportunities and challenges will presumably stay. And while the forms may change (e.g., social networks or microblogs were not present 15 years ago), the main challenges associated with cognitive and affective processing, namely integration and evaluation, stay the same. We conclude that it is imperative that we systematically advance our knowledge of which individual difference factors make it harder or easier for students to cope with these challenges and benefit from the opportunities, also in light of seeing which might be more (e.g., epistemic beliefs, reading skills and strategies), or less (e.g., working memory capacity) educationally malleable.</div></div>","PeriodicalId":48336,"journal":{"name":"Learning and Individual Differences","volume":"124 ","pages":"Article 102801"},"PeriodicalIF":9.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145424791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing argumentative writing with data-driven learning: Exploring developmental trajectories and learner profiles","authors":"Wenjuan Qin,&nbsp;Weiran Wang,&nbsp;Yongyan Zheng","doi":"10.1016/j.lindif.2025.102800","DOIUrl":"10.1016/j.lindif.2025.102800","url":null,"abstract":"<div><div>This study examines the effectiveness of a data-driven learning (DDL) intervention in enhancing EFL learners' argumentative writing skills. The research has two primary objectives: 1) to examine developmental trajectories of EFL learners' argumentative writing at lexical, syntactic, and organizational levels; 2) to identify distinct learner profiles that emerge based on the development of these linguistic measures. 199 EFL students participated in seven iterative cycles of argumentative writing assignments, followed by corpus-based analysis and personalized feedback. Results revealed diverse developmental paths across three linguistic levels. Three distinct learner profiles emerged: high-performing formal language users, functional language adventurers, and low-performing formal and functional language users. The findings highlight the dynamic, non-linear nature of language development and underscore the need for personalized instructional strategies and sustained support for higher-order writing skills. This study bridges research and practice gaps through an innovative researcher-practitioner partnership, providing valuable insights for optimizing DDL interventions in language education.</div></div>","PeriodicalId":48336,"journal":{"name":"Learning and Individual Differences","volume":"124 ","pages":"Article 102800"},"PeriodicalIF":9.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145120054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The future of personalized learning with AI","authors":"Jan L. Plass,&nbsp;Fabian Froehlich","doi":"10.1016/j.lindif.2025.102813","DOIUrl":"10.1016/j.lindif.2025.102813","url":null,"abstract":"<div><div>Personalized learning has the potential to enhance learning outcomes but faces challenges such as problems measuring learning variables, the lack of theoretical guidance for interventions based on these variables, and ethical considerations. The availability of new AI tools, including generative AI based on large language models (LLMs), has resulted in claims that the problem of personalization has been solved. The goals of this paper are to provide a shared, systematic language for describing adaptivity, adaptability and personalization of learning environments; to broaden how we conceptualize personalization; to define the adaptation cycle; and to discuss which aspects of the cycle can be supported by AI. Also discussed are levels of AI integration, and a proposed architecture for AI-based personalized learning environments.</div></div><div><h3>Education relevance</h3><div>The personalization of learning, i.e., the accommodation of every person's individual needs during the learning process, has been a goal for educators and learning environment designers alike. However, achieving this goal has been a challenge as key aspects of the personalization cycle face challenges, such as the measurement of learning variables and the lack of theoretical guidance for interventions based on these variables. We also need to consider ethical considerations related to unintended consequences of personalization. In this paper, we aim to deepen the discourse about personalized learning by defining key terms, showing how to broaden current conceptualizations of personalization to include affect, motivation, and socio-cultural variables, and providing terminology for the adaptivity cycle that allows for a more conceptual clarity. We then discuss how AI can support personalization of learning, with a focus on applications beyond chatbots. We introduce levels of AI integration in personalization and discuss an architecture that may enable personalization of learning through generative AI.</div></div>","PeriodicalId":48336,"journal":{"name":"Learning and Individual Differences","volume":"124 ","pages":"Article 102813"},"PeriodicalIF":9.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145333072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Differential use and effectiveness of practice testing: Who benefits and who engages?","authors":"Jakob Schwerter ,&nbsp;Fani Lauermann ,&nbsp;Taiga Brahm ,&nbsp;Kou Murayama","doi":"10.1016/j.lindif.2025.102761","DOIUrl":"10.1016/j.lindif.2025.102761","url":null,"abstract":"<div><div>Practice testing is an effective learning strategy, yet low-achieving students often underutilize it despite its benefits. This study investigates who benefits from and who engages in practice testing within an authentic educational setting. We collected data from 325 undergraduates (56 % self-identified as female) in a gateway mathematics course, combining survey responses, practice testing records, and exam performance (points, grades, passing). Employing regressions and prediction rule ensembles, we analyzed a comprehensive set of predictors (prior/current achievement, motivational beliefs, personality, and volitional factors). Increased practice testing was linked to improved exam performance, especially for students with moderate-to-high current achievement. Students with lower prior achievement were less likely to test themselves and required more practice testing attempts to achieve similar exam performance improvements. Predictors of practice testing included prior achievement, intrinsic value, and mastery goals. Therefore, integrating low-stakes testing with motivation-supportive interventions may reduce performance gaps and promote equity in higher education.</div></div>","PeriodicalId":48336,"journal":{"name":"Learning and Individual Differences","volume":"123 ","pages":"Article 102761"},"PeriodicalIF":9.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144771851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Skill learning as a predictor of literacy abilities and related impairments among second-graders from low-SES","authors":"Chagit Hollander ,&nbsp;Shoshi Dorfberger ,&nbsp;Michal Hochhauser ,&nbsp;Esther Adi-Japha","doi":"10.1016/j.lindif.2025.102779","DOIUrl":"10.1016/j.lindif.2025.102779","url":null,"abstract":"<div><div>This longitudinal study tested a conceptual model involving children's motor-skill learning, cognitive measures, and word-level literacy measures as predictors of higher levels of literacy skills. Motor skill learning was assessed with the Invented Letter Task (ILT), representing procedural learning. Second graders (<em>n</em> = 124) from low-SES schools practiced skill-learning across two consecutive days and two weeks later. Midway through the year, fine-motor coordination, working memory, phonological awareness, vocabulary, spelling, writing, and reading fluency were assessed. National standardized literacy tests were administered at the end of the school year. Using structural equation modeling, skill-learning first-day achievements (signifying learning) and two-week post-training performance (signifying automaticity), along with measures assessed midyear, served as predictors of reading comprehension and written expression, confirming the contribution of skill-learning to literacy acquisition. The risk for impairments in reading comprehension/written expression was tested using the same model, indicating similar, but not identical, associations.</div></div><div><h3>Educational relevance statement</h3><div>This study underscores the importance of skill-learning abilities for literacy development in second-grade children from low-income families. By using a letter-writing task, end-of-year reading and writing performance were predicted. The research identified key factors that may indicate which children are at risk for literacy impairments, emphasizing the need for early interventions. Early training in basic skills is shown to have significant long-term educational benefits. These findings suggest that educators can use such tasks to screen and support students, thereby improving literacy outcomes.</div></div>","PeriodicalId":48336,"journal":{"name":"Learning and Individual Differences","volume":"123 ","pages":"Article 102779"},"PeriodicalIF":9.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144988604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}