Search Results (54)

This study investigates the integration of learning theories with personalized technologies, focusing on the use of Augmented Reality (AR) in reading instruction. Its primary aim is to conduct a systematic literature review of research employing AR to support readers with the complexities of the reading process. The review focuses on literacy development in children from kindergarten through age twelve, encompassing both typically developing readers and those with reading difficulties. It is suggested that AR can contribute to inclusive education by offering adaptable and engaging learning experiences that meet diverse learner needs. Guided by clearly defined inclusion and exclusion criteria, the study analyzes key elements of research design, the types of AR technologies utilized, and the educational outcomes reported. Furthermore, it critically examines the limitations of the current body of evidence in this field. Full article

Background/Objectives: The Seeds of Literacy project has followed infants at family risk for dyslexia (FR group) and infants not at family risk (NFR group) since the age of 5 months, exploring whether infant measures of auditory sensitivity and phonological skills are related to later reading achievement. Here, we retrospectively assessed relations between infant performance on a rise time discrimination task with new pre-reading behavioural measures administered at 60 months. In addition, we re-classified dyslexia risk at 60 months and again assessed relations to rise time sensitivity. Participants were re-grouped using the pre-reading behavioural measures as either dyslexia risk at 60 months (60mDR) or no dyslexia risk (60mNDR). Methods: FR and NFR children (44 English-learning children) completed assessments of rise time discrimination at 10 and/or 60 months, phonological awareness, phonological memory, rapid automatised naming (RAN), letter knowledge, and language skills (receptive vocabulary and grammatical awareness). Results: Longitudinal analyses showed significant time-lagged correlations between rise time sensitivity at 10 months and both RAN and letter knowledge at 60 months. Rise time sensitivity at 60 months was significantly poorer in those children re-grouped as 60mDR, and rise time sensitivity was significantly related to concurrent phonological awareness, RAN, letter knowledge, and receptive vocabulary, but not to tests of grammatical awareness. Conclusions: The data support the view that children’s rise time sensitivity is significantly related to their pre-reading phonological abilities. These findings are discussed in terms of Temporal Sampling theory. Full article

As new technologies shape education, helping students develop historical consciousness remains a challenge. Building on Nordic curricula that emphasize students as both “history-made” and “history-making” citizens, this paper proposes an approach that integrates artificial intelligence (AI) with implicit digital game-based learning (DGBL) to learn and develop historical consciousness in education. We outline how traditional, lecture-driven history teaching often fails to convey the abstract principles of historicity (the idea that individual identity, social institutions, values, and ways of thinking are historically conditioned) and the interpretation of the past, understanding of the present, and perspective on the future. Building on Jeismann’s definition of historical consciousness, we identify a gap between the theory-rich notions of historical consciousness and classroom practice, where many educators either do not recognize it or interpret it intuitively from the curriculum’s limited wording, leaving the concept generally absent from the classroom. We then examine three theory-based methods of enriching teaching and learning. Game-based learning provides an interactive environment in which students assume roles, make decisions, and observe consequences, experiencing historical consciousness instead of only reading about it. AI contributes personalized, adaptive content: branching narratives evolve based on individual choices, non-player characters respond dynamically, and analytics guide scaffolding. Implicit learning theory suggests that embedding core principles directly into gameplay allows students to internalize complex ideas without interrupting immersion; they learn by doing, not by explicit instruction. Finally, we propose a model in which these elements combine: (1) game mechanics and narrative embed principles of historical consciousness; (2) AI dynamically adjusts challenges, generates novel scenarios, and delivers feedback; (3) key concepts are embedded into the game narrative so that students absorb them implicitly; and (4) follow-up reflection activities transform tacit understanding into explicit knowledge. We conclude by outlining a research agenda that includes prototyping interactive environments, conducting longitudinal studies to assess students’ learning outcomes, and exploring transferability to other abstract concepts. By situating students within scenarios that explore historicity and temporal interplay, this approach seeks to transform history education into an immersive, reflective practice where students see themselves as history-made and history-making and view the world through a historical lens. Full article

The authors conducted two experiments to assess the alignment between Generative AI (GenAI) text personalization and hypothetical readers’ profiles. In Experiment 1, four LLMs (i.e., Claude 3.5 Sonnet, Llama, Gemini Pro 1.5, and ChatGPT 4) were prompted to tailor 10 science texts (i.e., biology, chemistry, and physics) to accommodate four different profiles varying in knowledge, reading skills, and learning goals. Natural Language Processing (NLP) was leveraged to evaluate the GenAI-adapted texts using an array of linguistic and semantic features empirically associated with text readability. NLP analyses revealed variations in the degree to which the LLMs successfully adjusted linguistic features to suit reader profiles. Most notably, NLP highlighted inconsistent alignment between potential reader abilities and text complexity. The results pointed toward the need to augment the AI prompts using personification, chain-of-thought, and documents regarding text comprehension, text readability, and individual differences (i.e., leveraging RAG). The resulting text modifications in Experiment 2 were better aligned with readers’ profiles. Augmented prompts resulted in LLM modifications with more appropriate cohesion features tailored to high- and low-knowledge readers for optimal comprehension. This study demonstrates how LLMs can be prompted to modify text and uniquely demonstrates the application of NLP to evaluate theory-driven content personalization using GenAI. NLP offers an efficient, real-time solution to validate personalized content across multiple domains and contexts. Full article

The COVID-19 pandemic necessitated an urgent shift to emergency remote learning, significantly affecting the education of bilingual students. This study examines the use of technology-enhanced drama-based methods, specifically digital Readers Theater, as an emergency measure to enhance reading literacy and psychosocial support during the pandemic amid multiple concurrent crises. Using an action research approach, 37 Greek teachers implemented remote literacy activities involving digital drama in their virtual classrooms over a period of four weeks. Data were collected from semi-structured interviews, teachers’ reflective journals, and student participation and were analyzed through Ajzen’s Theory of Planned Behavior. The findings indicate that, despite technological challenges and adaptation difficulties, the creative use of digital drama activities contributed to improvements in students’ reading skills, motivation, and engagement. The intervention also fostered students’ emotional expression and social connection, contributing to their psychosocial support during the disruption. This study highlights the dual role of technology as both an enabler and a barrier, emphasizing the need for better digital infrastructure and comprehensive teacher training for effective emergency response. The results stress the value of technology-supported, arts-based approaches in maintaining student engagement and promoting bilingual literacy in crisis contexts. These findings provide useful guidance for teachers and school leaders on how to support students’ learning and well-being, both during crises and in everyday practice. Full article

The rapid rise of digital media and the accelerated pace of modern life have triggered a “reading crisis” among college students in China, which is characterized by declining deep reading abilities and increasing reliance on fragmented digital content. Understanding the multifaceted factors influencing student reading behavior is crucial for improving educational outcomes and fostering lifelong learning skills. This study examines these factors in China’s top universities using an ecological systems theory framework, which considers how individual attributes (micro), university environment (mezzo), and broader social contexts (macro) interact to shape reading behavior. This study analyzed a logistic regression model based on 1667 samples from 19 top universities in China, followed by cross-analysis using contingency tables. The findings highlight the significant impact of both individual and environmental factors on reading engagement and reveal the mediating role of university policies and resources in fostering students’ reading proficiency. Full article

This study examines the relationship between school climate, motivation, and academic emotions in shaping learning outcomes, with a focus on reading comprehension. Based on the control–value theory of academic emotions and self-determination theory, it explores how students’ perceptions of a caring school community and a positive learning climate influence their emotions, motivation, learning strategies, and reading performance. A total of 296 fifth- and sixth-grade students completed self-report measures assessing these factors. For the collection of the data, the participants completed the following scales: Motivation for Reading Questionnaire—MRQ, Achievement Emotions Questionnaire Pre-Adolescents (AEQ-PA), Learning Climate Questionnaire (LCQ), School as a Caring Community Profile-II-(SCCP-II), learning strategies questionnaire, and reading comprehension. The correlation and path analysis results revealed that students who viewed their school as supportive experienced more positive academic emotions and fewer negative ones. Positive emotions were linked to higher intrinsic and extrinsic reading motivation, while negative emotions correlated with lower motivation and disengagement. Intrinsic motivation significantly predicted deep learning strategies and improved reading comprehension, whereas the absence of learning strategies negatively impacted performance. These findings underscore the role of a supportive school environment in fostering motivation and emotional engagement. The educational implications of this study highlight the need for teaching practices that cultivate positive emotions, intrinsic motivation, and effective learning strategies to enhance reading comprehension and overall academic success. Full article

In the oil and gas IIoT environment, fire detection systems heavily depend on fire sensor data, which can be prone to inaccuracies due to faulty or unreliable sensors. These sensor issues, such as noise, missing values, outliers, sensor drift, and faulty readings, can lead to delayed or missed fire predictions, posing significant safety and operational risks in the oil and gas industrial IoT environment. This paper presents an approach for handling faulty sensors in edge servers within an IIoT environment to enhance the reliability and accuracy of fire prediction through multi-sensor fusion preprocessing, machine learning (ML)-driven probabilistic model adjustment, and uncertainty handling. First, a real-time anomaly detection and statistical assessment mechanism is employed to preprocess sensor data, filtering out faulty readings and normalizing data from multiple sensor types using dynamic thresholding, which adapts to sensor behavior in real-time. The proposed approach also deploys machine learning algorithms to dynamically adjust probabilistic models based on real-time sensor reliability, thereby improving prediction accuracy even in the presence of unreliable sensor data. A belief mass assignment mechanism is introduced, giving more weight to reliable sensors to ensure they have a stronger influence on fire detection. Simultaneously, a dynamic belief update strategy continuously adjusts sensor trust levels, reducing the impact of faulty readings over time. Additionally, uncertainty measurements using Hellinger and Deng entropy, along with Dempster–Shafer Theory, enable the integration of conflicting sensor inputs and enhance decision-making in fire detection. This approach improves decision-making by managing sensor discrepancies and provides a reliable solution for real-time fire predictions, even in the presence of faulty sensor readings, thereby mitigating the fire risks in IIoT environments. Full article

We enjoyed reading Jan Hustijn’s update of his Basic Language Cognition (BLC) theory in the pages of Languages (Hulstijn, 2024), and we are honored to provide a commentary here. Researchers, language learners, and educators hold varying definitions and understandings of language proficiency. Innovative work that helps researchers in the field rethink proficiency is therefore of utmost importance. Hulstijn’s BLC theory offers a clear, well-motivated, and comprehensive framework for investigating what language proficiency may be, what ceilings there may be in what can be attained, and what causes there may be for attainment differences. Hulstijn tells us that BLC rests on a metatheory (i.e., a foundation of assumptions) of language and language learning grounded in two areas familiar to most scholars in second language acquisition (SLA): usage-based linguistics and complex systems. He offers BLC as a theory, that is, a tool to empirically investigate the causation and development of a phenomenon, in this case, proficiency, through a well-articulated research program. In this commentary, we highlight some aspects of the updated BLC theory that we find most useful. Following the Popperian spirit embraced by Hulstijn, we also introduce some critical probes subjects for refinements that may benefit BLC theory in the future. Full article

This article is about how Elsa, a young Sámi girl in Ann-Helén Laestadius’ Stolen, learns to resist hate crimes that seek to sever her roots in traditional Indigenous herding practices. The nine-year old Elsa witnesses the killing of her personal reindeer and is threatened into a decade-long silence by the killer. There are more attacks which we read as the violent enforcement of western linear time on traditional seasonal herding cycles. The novel charts Elsa’s coming-of-age as a rebel able to seek retribution not just for herself and her reindeer but also to fight for a vital future for her culture. We read Stolen together with “revolutionary theory” to show how imposed settler temporality is harmful to sustainable modes of living. We emphasise a range of eco-activist responses to the novel, among them rebel reading itself as one of several forms of political engagement available for the eco-rebel. We consider teaching Stolen at secondary school level focusing on how readers can practice risk-taking engagement with a text while learning “how to read our world now” in solidarity with Elsa’s struggle for her people’s survival within an ecologically and socially just future for all. Ultimately, Elsa’s emergent rebellion suggests forms of activism based on a commitment to ancestry, especially its future. Full article

Collaboration plays an important role in educational contexts. However, little is known about students’ metacognitive beliefs about collaboration. The present study used an online survey to investigate students’ beliefs toward group study/recall, their studying preferences, strategies they use when studying individually and in groups, and important characteristics of their group members. Results indicate that, although students generally perceive collaboration as beneficial, they prefer individual study, indicating that their beliefs are inconsistent with their learning preferences. Students report social learning as the primary reason for collaborative benefits but prefer to study alone to minimize distraction and increase personal accountability. Further, they use different strategies when studying individually or in a group. When studying individually, students most frequently report re-reading their notes. However, when studying in groups, students most frequently use strategies emphasizing collaboration and interaction, such as quizzing each other. Also, students prefer to work with group members who are focused, motivated, and hard working. Students’ beliefs, preferences, and favored characteristics of group members are related to their frequency of using study groups. Students’ metacognitive beliefs about collaboration have implications for theories of self-regulated learning and better use of collaboration in educational contexts. Full article

The past two years saw a rapid proliferation of information and communication technologies (ICTs) in higher education. Digital technologies and environments offer many affordances. New digital literacy practices in universities have implications for teaching and learning. E-textbooks, in particular, act as mediating tools that can facilitate teaching and learning through developing students’ understandings of scientific concepts. This paper positions e-textbooks as mediators of learning, rather than merely objects of learning. There is thus a need to understand the mediating role of e-textbooks that lecturers draw on in their teaching. While much research was conducted on students’ use of e-textbooks, relatively little was conducted on lecturers’ use of e-textbooks in engineering education. The current study aimed to answer the following research question: What are lecturers’ perspectives on the use of e-textbooks to facilitate learning in engineering? To address this question, data were collected through five individual interviews conducted with engineering lecturers working in the Extended Curriculum Programme (ECP) of first-year students from three engineering departments (chemical engineering, mechanical engineering, and nautical science) at a university of technology in South Africa. The data were analysed using thematic content analysis with the help of ATLAS.ti. Data analysis was guided by a theoretical framework that drew on the cultural-historical activity theory (CHAT). In this study, the focus was on e-textbooks as pedagogical tools within engineering teaching and learning. The findings provide insight into how lecturers incorporate e-textbooks into their teaching, but also reveal the extent to which new digital literacy reading practices remain unfamiliar to engineering lecturers. CHAT enabled the identification of a critical insight, namely, the tension between mediation and division of labour. This highlights important aspects of the discourse surrounding seamless technology integration in higher education. The discussion points to the need for an expansive transformation regarding the use of e-textbooks as important mediating tools for teaching and learning. Full article

The focus of the present paper is twofold; the first objective is to examine how children with dyslexia (henceforward DYS children) and typically developing children (henceforward TD children) performed in Greek (first language; L1) compared to English (second language; L2) in reading, phonological awareness (PA), rapid automatized naming (RAN), working memory (WM), and short-term memory (STM) tasks. Our second goal is to investigate DYS children’s performance compared to that of TD children in the L1 and L2 domains mentioned above. Thirty-two (DYS = 16; TD = 16) school-aged children (9;7–11;9 years old; M_age = 130.41), basic users of English (level ranging from A1 to A2), carried out a battery test in L1 and L2, respectively, including reading, PA, STM, and WM tasks. More specifically, the tasks were the following: word and nonword decoding, reading accuracy and reading fluency, word and nonword reading per minute, PA, RAN, nonword repetition, as well as forward, backward, and digit span sequencing. This is a work-in-progress study, and preliminary results reveal that DYS students exhibit important reading and memory deficits in both languages. The data analysis indicated that DYS children have particular difficulties and statistically significant differences in L1 and L2 compared to TD in all tasks. In conclusion, this is the first study, at least in Greek, which assesses both reading and memory skills of DYS children in L2. The results reveal deficits in both languages, and the overall findings contribute to theories on the transfer of difficulties of linguistic skills between L1 and L2, while memory scores also underline this co-occurrence. Future implications of this study include a combination of reading and cognitive activities in the teaching methods of English teachers to improve DYS children’s overall performance in learning English as L2. Full article

In this conceptual paper, we present a discussion of how we have embraced two challenges, posed by Aukerman and Schuldt, in their call for a more socially just science of reading, to which this special issue is responsive. Specifically, we share lessons learned from years of designing texts that (a) advance knowledge-building in the context of project-based science teaching and (b) advance readers’ textual dexterity. Our research is conducted in the context of project-based learning in science, and we approach our inquiry from multiple theoretical perspectives. We argue for the importance of text in science instruction. We present theories, empirical support, and national standards consistent with the integration of text in science. We discuss the role that texts can play in project-based science instruction. We also illustrate the design and optimization of texts and tasks, as well as the role of the teacher in this instruction. Full article

BLC Theory proposes that individual differences (IDs) in language proficiency (in both native and non-native speakers) can poorly be mapped on a single proficiency scale. Instead, IDs can best be understood and studied in terms of two fundamentally different dimensions: (1) the cognition of oral language (receptive and productive speech processing) and (2) the cognition of the written language (reading and writing). This paper presents an update of BLC Theory placed under a non-nativist, usage-based, neural-network metatheory of language as a complex system. The paper includes predictions for the absence or presence of IDs in the oral and written domains, separately for native and non-native speakers. The theory predicts that while cognitive factors such as executive functions, non-verbal memory, and intelligence positively affect the acquisition of reading and writing skills in both native and non-native speakers, they do not play a significant role in the acquisition of speech processing in either native or non-native speakers. Contrary to folk wisdom, one does not need to be particularly intelligent to learn to understand and produce speech in a non-native language. Attention is given to typological differences between children’s home language(s) and the standard language(s) of literacy. Full article