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To trace the evolution of research strands in published Computer Assisted Language Learning (CALL) papers over time, a corpus of 426 highly-cited papers in four major CALL journals ("ReCALL," "CALL," "LL&T," and "CALICO Journal") was compiled and coded using NVivo 12. All identified aspects of technology-mediated language learning and teaching were collected to produce a comprehensive list of 690 recurring research strands and then, by adopting a constant comparison method, were merged to form 119 unique research strands. The top 10 alone represent almost half of all research strands: Computer-Mediated Communication (CMC), writing, vocabulary, feedback, evaluation, learning environment, telecollaboration, design, speaking, and grammar. This paper provides the rationale for the study along with the methodology for data collection and analysis, with a particular focus on the dominant and intermediary strands to inform future CALL publications. [For the complete volume, "Intelligent CALL, Granular Systems and Learner Data: Short Papers from EUROCALL 2022 (30th, Reykjavik, Iceland, August 17-19, 2022)," see ED624779.]

The world of Computer Assisted Language Learning (CALL) is dominated by English, and to a lesser extent, French, Spanish, and German. While these languages are the main focus of EUROCALL conferences, there has always been a presence of Less Commonly Taught Languages (LCTLs) at these conferences. Most of the official languages of the EU and European languages more generally have been discussed by CALL researchers at EUROCALL conferences, but some languages have yet to make an appearance. There have also been presentations on other LCLTs outside of Europe, including Mandarin, Arabic, Japanese, and less widely spoken languages such as Thai and Nahuatl. This paper looks at the presence of LCTLs at EUROCALL conferences since 1993 and reflects on what has changed over the years. It notes the importance of the conference location on the languages discussed at the conference and the role of EU projects in supporting LCTLs. [For the complete volume, "CALL and Professionalisation: Short Papers from EUROCALL 2021 (29th, Online, August 26-27, 2021)," see ED616972.]

Access to body-based resources has been shown to augment cognitive processes, but not all movements equally aid reasoning. Interactive technologies, like dynamic geometry systems (DGS), potentially amplify the link between movement and geometric representation, thereby deepening students' understanding of geometric properties. This study investigated the influence of access to a DGS on students' geometric reasoning and gesture production compared to the impact of only spontaneous gestures. Access to simulations did not significantly increase the likelihood of students producing correct mathematical insights compared to spontaneous gestures. However, when controlling gesture production, DGS access became a significant predictor for transformational proof production. We also found that access to DGS influenced the type of gestures students produced during geometric reasoning tasks. This study underlines the vital role of gestures in geometric reasoning and suggests that while DGS offers benefits, spontaneous gestures remain a crucial embodied resource for exploring geometric concepts. [This paper was published in: "Proceedings of the 18th International Conference of the Learning Sciences - ICLS 2024," edited by R. Lindgren et al., International Society of the Learning Sciences, 2024, pp. 131-38.]

With an increase in Synchronous online learning, there is a shift in how current teaching practices are impacted and what is important to students and student learning. Synchronous teaching is not taking face-to-face strategies online, instead, it requires intentional design and thoughtful planning. To that end, this paper discusses pedagogical strategies for designing online spaces that create, cultivate and sustain social presence. Literature and research that support the connection between social presence and student learning will be shared, including the presenters' recently published text "Effective Learning Environments in Higher Education Online Settings: Establishing Social Presence." The framework presented in this text separates Social presence into three themes: social climate, membership in a learning community, and students feeling real. In this paper, authors elaborate on how instructors can build community in online courses. [For the full proceedings, see ED652228.]

This paper discusses the distribution, through a digital datacasting framework, of mathematical resources for Grades 1 to 7 to two schools in a community in the Philippines. Among the mathematical resources made available, are mathematical applications (apps), which run on mobile technologies, that have been created to help in the mathematical learning of students in a remote setting. The distribution is facilitated by the RuralCasting set-top box, a developed custom set-top box capable of receiving digital TV broadcasts and providing local content access through its Wi-Fi network. This paper presents the performance of the set-top box in distributing the mobile mathematical apps, and a short discussion on the mathematical applications deployed. [For the full proceedings, see ED639391.]

This paper introduces "FineTune," a mobile application currently in development that features a gamified version of High Variability Phonetic Training (HVPT). The aims of this paper are twofold: (1) to outline the theoretical motivation for the app's features, which includes a discussion of HVPT, gamification, and Self-Determination Theory (SDT), and (2) to describe how "FineTune" functions as a mobile application, considering the theories that informed its design. [For the complete volume, "Intelligent CALL, Granular Systems and Learner Data: Short Papers from EUROCALL 2022 (30th, Reykjavik, Iceland, August 17-19, 2022)," see ED624779.]

This paper presents a reflection on the design of an Intelligent Computer-Assisted Language Learning (ICALL) 'ecosystem', integrated into an online learning environment for Spanish as a Foreign Language (SFL). The innovative dimension of the ecosystem lies in its triple focus: apart from enabling users to create and use intelligent language learning materials, it also tracks their activities in the environment and provides them insights (e.g. through knowledge clips) into Natural Language Processing (NLP), the source of ICALL's 'intelligence'. The reflective analysis is carried out by means of a case study with 32 SFL students, who work with the ecosystem in a blended writing course focused on vocabulary learning, lexical ambiguity, and Word Sense Disambiguation (WSD). Students' attitudes towards engaging in the ICALL ecosystem are gauged through a questionnaire, which revealed a statistically significant positive change in attitude after having completed the course. However, the results also show that enhanced insights into NLP and increased confidence in the computer as a learning assistant do not necessarily go hand in hand with an increased curiosity and a better user experience. [For the complete volume, "Intelligent CALL, Granular Systems and Learner Data: Short Papers from EUROCALL 2022 (30th, Reykjavik, Iceland, August 17-19, 2022)," see ED624779.]

Game Based Language Learning (GBLL) is an approach to language learning in which learning happens in the process of playing a game. GBLL has several potential benefits including enhanced reading, writing, and cultural awareness. This paper provides a brief overview of Cipher -- Faoi Gheasa, a GBLL app for Irish and learners' feedback on the game. The app inverts the current Intelligent Computer Assisted Language Learning (ICALL) approach to error detection and it asks players (learners) to spot the deliberate errors (ciphers) in texts that have been changed by an evil character called Sypher. Many elements of game playing are included in the app. It has been played by over 150 primary school learners of Irish. While there is still room for improvement, the overall feedback from the students was very positive. [For the complete volume, "Intelligent CALL, Granular Systems and Learner Data: Short Papers from EUROCALL 2022 (30th, Reykjavik, Iceland, August 17-19, 2022)," see ED624779.]

This paper explores the use of a Computer Assisted Language Learning (CALL), growth mindset infused, student partnership approach to language learning in a primary school context. Early success is important in language learning. Students may doubt their ability to learn a language, especially if they have had a non-positive experience of learning a language. This research study looks at a research intervention for learning Spanish in an Irish primary school. A combination of in-class and CALL resources were used to teach Spanish in six sessions to 120 students from six different classes (10-12 years of age), all of whom were beginners. Most had learnt Irish since four or five years of age and had no previous exposure to CALL, growth mindset, or a student partnership. There were several logistical hiccups along the way, including a low response rate to the end of intervention survey (via questionnaire). However, the overall indications are that the students enjoyed the approach and that it could be used in other contexts. [For the complete volume, "Intelligent CALL, Granular Systems and Learner Data: Short Papers from EUROCALL 2022 (30th, Reykjavik, Iceland, August 17-19, 2022)," see ED624779.]

"An Corpas Cliste" ('Clever Corpus') is an Irish language learner corpus. The corpus data comes from a purpose-built intelligent Computer Assisted Language Learning (iCALL) platform called "An Scéalaí" ('the Storyteller') and comprises both audio and text, produced by second and third level learners of Irish. Metadata (e.g. L1, level of Irish, dialect preference, age) is saved with every learner account, along with data on platform engagement (e.g. speech/language technologies employed, time spent on task). This paper illustrates how "An Corpas Cliste" is structured and is being prepared for analysis and the methodologies and resources that are being used to exploit it with a view to enhancing the learning experience. [For the complete volume, "Intelligent CALL, Granular Systems and Learner Data: Short Papers from EUROCALL 2022 (30th, Reykjavik, Iceland, August 17-19, 2022)," see ED624779.]

While previous studies have established the significance of CALL (Computer-Assisted Language Learning) in language education, the extent to which CALL influences language teachers' well-being and their professional development has not yet been fully understood. This echoes Dörnyei's (2018) argument that although language teachers are the most important factors in learners' success, their contributions have not been considered sufficiently. As such, this short paper presents an ongoing mixed-methods project investigating Vietnamese and Japanese language teachers' well-being and the role of CALL in the ecology of language teaching at both personal and work levels using Bronfenbrenner's (1979) ecological system framework. The primary method is the grounded theory analysis and preliminary results from Vietnamese teachers' semi-structured interviews which have shown the importance of CALL in language teachers' well-being's ecology. Also, the role of the community of practice has also emerged as an informal support in language teachers' ecological well-being system. [For the complete volume, "Intelligent CALL, Granular Systems and Learner Data: Short Papers from EUROCALL 2022 (30th, Reykjavik, Iceland, August 17-19, 2022)," see ED624779.]

Language researchers and teachers have long been interested in the timing of learning, and the distributed practice effect, whereby greater inter-session intervals result in longer retention, is well-known (Kim & Webb, 2022). Many L2 studies have focused on the intentional learning of lexis (Edmonds, Gerbier, Palasis, & Whyte, 2021), neglecting implicit learning and syntactic development (Rogers, 2021). The present project includes both explicit vocabulary learning activities and incidental exposure to a complex syntactic structure via a bespoke online L2 English learning platform. The goal is to investigate the two types of learning in two spacing conditions. This paper describes (1) the learning activities created to present opportunities for explicit vocabulary learning and the concealed syntactic input, and (2) the tests used to evaluate participants' receptive and productive knowledge of target items. It aims to inform computer assisted language learning design with respect to pedagogical progression, learning activities, feedback, and learning schedules. [For the complete volume, "Intelligent CALL, Granular Systems and Learner Data: Short Papers from EUROCALL 2022 (30th, Reykjavik, Iceland, August 17-19, 2022)," see ED624779.]

Transactive discussion during collaborative learning is crucial for building on each other's reasoning and developing problem solving strategies. In a tabletop collaborative learning activity, student actions on the interface can drive their thinking and be used to ground discussions, thus affecting their problem-solving performance and learning. However, it is not clear how the interplay of actions and discussions, for instance, how students performing actions or pausing actions while discussing, is related to their learning. In this paper, we seek to understand how the transactivity of actions and discussions is associated with learning. Specifically, we ask what is the relationship between discussion and actions, and how it is different between those who learn (gainers) and those who do not (non-gainers). We present a combined differential sequence mining and content analysis approach to examine this relationship, which we applied on the data from 32 teams collaborating on a problem designed to help them learn concepts of minimum spanning trees. We found that discussion and action occur concurrently more frequently among gainers than non-gainers. Further we find that gainers tend to do more reflective actions along with discussion, such as looking at their previous solutions, than non-gainers. Finally, gainers discussion consists more of goal clarification, reflection on past solutions and agreement on future actions than non-gainers, who do not share their ideas and cannot agree on next steps. Thus this approach helps us identify how the interplay of actions and discussion could lead to learning, and the findings offer guidelines to teachers and instructional designers regarding indicators of productive collaborative learning, and when and how, they should intervene to improve learning. Concretely, the results suggest that teachers should support elaborative, reflective and planning discussions along with reflective actions. [For the complete proceedings, see ED630829.]

Spatial ability is frequently encountered in professional disciplines and daily life. In general, it includes abilities such as rotating objects, estimating the appearance of objects based on a person's position, and being able to think of open and closed forms of three-dimensional objects. It is essential in learning and teaching geometry. In this research, we tried to examine the spatial abilities of 6th grade students through Visualize-Predict-Check (VPC) heuristic in a computer-based environment (GeoGebra). In the research, we designed the teaching materials according to the topics such as reflection, translation, rotation, view from different directions, and expansion, which are included in the mathematics curriculum. The experimental method was used in the research, and the Spatial Reasoning Instrument (SRI) was used for pre-test and post-test. The research groups were 75 students selected from 223 6th grade students studying in four public secondary schools in a large province of the Black Sea Region during the 2022-2023 academic year. These students were selected according to their pre-test scores and were divided into three heterogeneous groups of 25 students each. The result of the research indicates that through the VPC heuristic, there was no statistically significant difference between the scores of the first group of students in the spatial reasoning instrument when teaching was carried out only according to the visualization component. However, there was a statistically significant difference between the scores of the second and third group students in the spatial reasoning instrument when teaching was carried out, respectively, according to the visualization prediction and visualization-prediction-control components. Based on the findings, suggestions were made for further research. [This paper was published in: "EJER Congress 2023 International Eurasian Educational Research Congress Conference Proceedings," Ani Publishing, 2023, pp. 538-553.]

Mobile devices, augmented reality (AR), and outdoor games can be mobilized to promote Education for Sustainable Development and, thus, to sensitize to nature conservation. The EduCITY project combines mobile learning, AR, and environmental sensors towards sustainability education and creates opportunities for citizens to contribute to their city's sustainability. This paper presents a study that articulates the previous project, the EduPARK, with the current one, the EduCITY. While EduPARK was developed within an urban park, EduCITY expanded its geographical area to the entire city. This study aims to analyze students' perceptions regarding changes in their nature conservation attitudes after exploring an urban green park in a mobile AR game-based learning activity. For this purpose, 233 basic education students (from school-year 5 to 9) played a game for environmental education, available in the EduPARK app, at the Infante D. Pedro Park (Aveiro, Portugal). Through a mixed method approach, data collection was focused on students and included two questionnaires, applied before and after the game activity; a focus group guide; and an observation grid. Results show a strengthening of positive attitudes towards nature conservation. Moreover, students mentioned that their nature conservation future intentions are focused on preserving natural resources, combating resources' waste, recycling waste, reducing pollution, and protecting fauna and flora. Students also revealed willingness and concern to teach friends and family about what they have learned with the EduPARK game. The EduCITY intends to give continuity to these practices throughout Aveiro city. This is anchored on a community-based participatory project integrating AR location games based on challenges, to be explored in the city, in formal, non-formal, and informal educational contexts, in a socio constructivism approach. This study adds to the literature on education for Sustainable Development, by revealing that it is possible to sensitize school students to nature conservation through mobile AR game-based approaches in the outdoors, which can be a first step to promote positive nature attitudes. [For the full proceedings, see ED639391.]

This article provides evidence of critical factors of student retention in Language Massive Open Online Courses (LMOOCs). The study used multiple sources: tracked retention data (n=43,000), survey data in correlation with tracking data (n=400), and qualitative data (174 informants) from a survey (Friðriksdóttir, 2018, 2021a, 2021b). The data came from learners in seven courses and across different delivery modes in the LMOOC program Icelandic Online (IOL, https:// icelandiconline.com). First, analysis of the tracking data revealed low overall completion rates and that retention was highest in the blended mode of delivery. The analysis also uncovered a specific dropout pattern and pattern of user engagement. Second, the survey study identified six content-related and four tutor-related engagement factors and that learners' differing goals for course participation influenced retention. Finally, qualitative data analysis revealed intrinsic and extrinsic motivational factors responsible for course completion, whereas non-course-related factors affected retention among dropouts. Overall, the study identified multi-ranged determinants of student retention. [For the complete volume, "Intelligent CALL, Granular Systems and Learner Data: Short Papers from EUROCALL 2022 (30th, Reykjavik, Iceland, August 17-19, 2022)," see ED624779.]

Linggle is a pattern-based referencing tool that assists in collocation learning. In this ongoing project, we aimed to improve its performance further. First, many of the example sentences are long and difficult for students to understand, so we used a machine learning method and trained a classifier to help select dictionarylike example sentences. Second, we created a database of 60,270,000 sentences from 4C, S2ORC, and VOA Learning English. We also included Google books for real-time supplements. Then, we applied the classifier to select good example sentences from the database for display. We also limited the number of example sentences displayed for search results to improve users' experiences. Two classes of English as a Foreign Language (EFL) college students (N=51) were invited to use the enhanced tool and filled out a questionnaire. The results showed that the students were positive about Linggle's new interface and the quality of the example sentences. We expect that more EFL learners will benefit from the tool. [For the complete volume, "Intelligent CALL, Granular Systems and Learner Data: Short Papers from EUROCALL 2022 (30th, Reykjavik, Iceland, August 17-19, 2022)," see ED624779.]

The attitudes of student-teachers to Computer Assisted Language Learning (CALL) remains an under-explored topic in research literature. This mixed-methods study engaged student-teachers in focus group discussions at commencement and completion of Initial Teacher Education (ITE). These student-teachers were situated across England, Scotland, Wales, and Northern Ireland. Student-teachers' beliefs regarding the perceived value of CALL experienced a considerable transformation between initial and follow-up focus group interactions. Beginning student-teachers collectively portrayed CALL in a complimentary light, with 67.5% of participant dialogue positively coded via thematic analysis. This contrasts with follow-up student-teacher discourse, where only 38.55% of nodes in NVivo were positively coded. Overall, belief changes were most marked for positive categories of CALL. Thus, maintaining optimistic opinions to CALL could be a worthwhile endeavour to promote student-teacher acceptance of digital technologies in language learning. [For the complete volume, "Intelligent CALL, Granular Systems and Learner Data: Short Papers from EUROCALL 2022 (30th, Reykjavik, Iceland, August 17-19, 2022)," see ED624779.]

This study reports on the development of "Parlure Games" and explores its pedagogical affordances. "Parlure Games" is a multi-dialectal listening and decolonial conversation tool created to address the absence of variable speech (including speech markers associated with native speaker status, regional dialect, age, and race) found in the audiovisual material of adult French learners in Montréal, Canada. "Parlure Games" enables instructors to curate audiovisual content inclusive of different social and regional dialects, and supports learners in understanding variable speech while self-locating themselves in the process of learning a colonial language. [For the complete volume, "Intelligent CALL, Granular Systems and Learner Data: Short Papers from EUROCALL 2022 (30th, Reykjavik, Iceland, August 17-19, 2022)," see ED624779.]

Modern language learning applications have become 'smarter' and 'intelligent' by including Artificial Intelligence (AI) and Machine Learning (ML) technologies to collect different kinds of data. This data can be used for analysis on a microscopic and/or macroscopic level to provide granulation of knowledge. We analyzed 1,213 French language learner data over a 30-day period, publicly available from Duolingo, to compare the progression of individual learners (microscopic granularity) and large groups of learners (macroscopic granularity). Using network modeling, we compared patterns of individual learners against one another and that of a learning community and determined what groups of learners typically practice across communities. Preliminary results suggest how applications for L2 learning can be designed to create an optimal path for learning. [For the complete volume, "Intelligent CALL, Granular Systems and Learner Data: Short Papers from EUROCALL 2022 (30th, Reykjavik, Iceland, August 17-19, 2022)," see ED624779.]

The present exploratory study investigated the efficacy of secondary face-to-face classroom-based English as a Foreign Language (EFL) instruction digitally supported by the FeedBook, an interactive computer assisted language learning web-based suite of exercises providing item-level scaffolded feedback. Seventy-seven native (L1) German seventh-grade students used the FeedBook during four two-week training periods (cycles, here we analyse Cycle 2 and 3). Classroom and FeedBook practice occurred in parallel, except for grammar constructions for which only FeedBook practice was provided (controls). At the end of Cycle 3, students engaged in a classroom-based communicative task for which the practised constructions were relevant. Custom-designed pre- and post-tests, administered via the FeedBook, assessed language accuracy in each cycle. Mixed-effect models revealed significant pre-/post-test accuracy gains independent of the learners' proficiency in English, but not in controls. Gains from digitally supported instruction were also positively related to accurate use of EFL grammar constructions in the communicative task. Overall, the results indicate learning benefits for face-to-face classroom-based instruction supported by the FeedBook, evidenced both in grammar tests and in communicative activities. [For the complete volume, "Intelligent CALL, Granular Systems and Learner Data: Short Papers from EUROCALL 2022 (30th, Reykjavik, Iceland, August 17-19, 2022)," see ED624779.]

This study examines the relationship between English language proficiency outcomes and the use of a Computer-Assisted Language Learning (CALL) tool that is designed to strengthen the academic English and oral proficiency skills of young English Learners (ELs). We compare scores on a standardized English language proficiency assessment for 2,034 ELs from kindergarten through Grade 5 in the US who either used the CALL tool during the 2020-2021 academic school year (n=1,478) or did not (n=556). Descriptive analyses show larger scores for students who used the program than those who did not, and this was seen across student demographic subgroups. Statistical analyses reveal that this difference is significant even when accounting for student demographics and enrolled school and that greater program use is related to higher proficiency scores. The largest effects are seen for oral proficiency scores. The study raises implications for use of CALL tools in contexts where English is the language of education. [For the complete volume, "Intelligent CALL, Granular Systems and Learner Data: Short Papers from EUROCALL 2022 (30th, Reykjavik, Iceland, August 17-19, 2022)," see ED624779.]

The current study investigated the role of visual short-term memory, working memory, and declarative memory as individual differences in the earliest stages of vocabulary and syntactic learning in "Duolingo"-based language instruction. Thirty-eight L1-Greek adults completed memory tasks and engaged in learning Navajo on "Duolingo." Subsequently, vocabulary and syntax were assessed respectively via a word recognition, a word translation, and a grammaticality judgement task. Multiple regression analyses revealed an advantage for distributed practice both in vocabulary and syntax, after controlling for amount of practice. Further, declarative memory played a significant role in learning syntax and vocabulary, when measured in a word translation task. Extending the analysis for the first time to app-based environments, the results of the present study confirm the importance of declarative memory and distributed practice in adult acquisition of L2 vocabulary and syntax. [For the complete volume, "Intelligent CALL, Granular Systems and Learner Data: Short Papers from EUROCALL 2022 (30th, Reykjavik, Iceland, August 17-19, 2022)," see ED624779.]

The use of chatbots in language learning has been on the rise. In recent Computer-Assisted Language Learning (CALL) research, there is a consensus that rule-based, scripted voice systems are optimal for language learning. Such systems integrate well into instructed language learning in that interactions with the user are predictable and controlled. Open, AI-based voice systems (such as in personal assistants like Siri) do not provide that degree of task-oriented learning. However, the argument is made here that they have the potential to provide open-ended conversational practice and language development which aligns with an ecological, usage-based perspective on language development. [For the complete volume, "Intelligent CALL, Granular Systems and Learner Data: Short Papers from EUROCALL 2022 (30th, Reykjavik, Iceland, August 17-19, 2022)," see ED624779.]

We are developing a Computer-Assisted Pronunciation Training (CAPT) system for learners of Icelandic as a second and foreign language (L2). Based on pre-designed tasks in pronunciation exercises, this system will provide corrective feedback on learners' speech. One of the main features we are implementing is a new method for automatic pronunciation scoring to provide immediate feedback on learners' errors. We report promising results for a pilot study of this method in Norwegian, where the pronunciation score successfully distinguishes between native speakers and adult learners, and we discuss how this method informs our continued development of Icelandic CAPT. [For the complete volume, "Intelligent CALL, Granular Systems and Learner Data: Short Papers from EUROCALL 2022 (30th, Reykjavik, Iceland, August 17-19, 2022)," see ED624779.]

We present a study in which multimedia alphabet books were constructed for ten languages using the Learning And Reading Assistant (LARA) platform. We describe the alphabet books we built, the different design features they instantiate, and an initial evaluation using an anonymous online questionnaire. Links are provided to the books themselves, which are freely available on the web. [For the complete volume, "Intelligent CALL, Granular Systems and Learner Data: Short Papers from EUROCALL 2022 (30th, Reykjavik, Iceland, August 17-19, 2022)," see ED624779.]

Reading comprehension is essential for students' ability to build knowledge. Students' comprehension abilities can be enhanced by providing students with deliberate practice and formative feedback on reading comprehension strategies. iSTART is an Intelligent Tutoring System (ITS) that is designed to provide instruction in reading strategies with minimal teacher supervision -- affording the ability to teach reading strategies at scale. In the current study, undergraduate students received reading strategy instruction and opportunities for deliberate practice via the iSTART intelligent tutoring system or not (i.e., no-treatment control group). Participants' reading comprehension and psychology knowledge were assessed. The iSTART group demonstrated substantially greater scores than the control group on a post-training reading comprehension measure (Cohen's d > 1.0). The average psychology knowledge scores did not differ between iSTART (post-training) and control groups, but overall these scores were unexpectedly low. Within the iSTART group, there was no difference in reading comprehension and knowledge scores as a function of students' different behaviors in the system. Overall, the results indicate that iSTART is an effective tool to teach reading strategies at large scale. However, further work is required to test the extent to which iSTART supports knowledge building. [This paper was published in: "Proceedings of Learning @ Scale conference (L@S '24)," ACM, 2024.]

This article's interest is to approach the impact and changes occurred by integrating digital pedagogical practices in the Moroccan higher educational system. The paper emphasizes the use of digital technology in the university curriculum, and how the latter shaped students' behavior as well as learning development. Our research methodology is based on observation sessions in which we measured and accessed students' knowledge acquisition, and how the use this digital learning in their research and study process. We also worked on focus groups with students of French department in the faculty of letters and human sciences of Agadir to measure how the digital learning process could increase student's creativity and critical thinking. This methodology is adopted in order to present an overview or the educational context and the appearing challenges in order to propose innovative work perspectives and to design a model of digital learning strategy enhancing student's analysis and interpretation competencies. The main concern of our paper is how can we integrate an innovative impactful digital strategy in the process of learning and teaching in higher education, knowing that this system remains somehow resilient? [For the full proceedings, see ED630948.]

The use of technology as a facilitator in learning environments has become increasingly prevalent with the global pandemic caused by COVID-19. As such, computer-supported collaborative learning (CSCL) gains a wider adoption in contrast to traditional learning methods. At the same time, the need for automated tools capable of assessing and stimulating collaboration between participants has become more stringent, as human monitoring of the increasing volume of conversations becomes overwhelming. This paper introduces a method grounded in dialogism for evaluating students' involvement in chat conversations based on semantic chains computed using language models. These semantic chains reflect emergent voices from dialogism that span and interact throughout the conversation. Our integrated method uses contextual information captured by BERT transformer models to identify links in a chain that connects semantically related concepts from a voice uttered by one or more participants. Two types of visualizations were generated to depict the longitudinal propagation and the transversal inter-animation of voices within the conversation. In addition, a list of handcrafted features derived from the constructed chains and computed for each participant is introduced. Several machine learning algorithms were tested using these features to evaluate the extent to which semantic chains are predictive of student involvement in chat conversations. [This paper was published in: "Ludic, Co-design and Tools Supporting Smart Learning Ecosystems and Smart Education, Proceedings of the 6th International Conference on Smart Learning Ecosystems and Regional Development," edited by Ó. Mealha et al., Springer Nature Singapore Pte Ltd., 2022, pp. 67-78.]

This paper focuses on Partial and Synchronized Caption (PSC) as a tool to train L2 listening and introduces new features to facilitate speech-related difficulties. PSC is an intelligent caption that extensively processes the audio and transcript to detect and present difficult words or phrases for L2 learners. With the new features, learners can benefit from repetition and slowdowns of particular audio segments that are automatically labeled difficult. When encountering high speech rates, the system slows down the audio to the standard rate of speech. For disfluencies in speech (e.g. breached boundaries), the system generates the caption and repeats that video segment. In our experiments, intermediate L2 learners of English watched videos with different captions and functionalities, provided feedback on new PSC features, and took a series of tests. Smart repetition and slowdown components received positive learner feedback and led to significant improvement in L2 listening recognition. [For the complete volume, "CALL and Professionalisation: Short Papers from EUROCALL 2021 (29th, Online, August 26-27, 2021)," see ED616972.]

This paper is an initial report of the data analysis phase of a larger study that traces the evolution of Computer Assisted Language Learning (CALL). All published Research Articles (RAs) from four major CALL journals -- "ReCALL," "CALL," "Language Learning & Technology" ("LL&T") and "CALICO Journal" -- from the very first issues to the end of 2019 were downloaded, sorted, and checked to form the final corpus of 426 highly cited RAs. The trends and themes (research contexts, research participants, and theoretical and methodological considerations of the RAs) were all recorded to see how CALL has evolved over time. Primary findings indicate that empirical studies where learners are physically or virtually involved in the process of technology-mediated language instruction dominate the field of CALL research. Authors resort to both quantitative and qualitative methodologies for data collection and analysis, though mixed-methods has gained more weight in the past two decades. Sociocultural theory stands over and above other theories in Second Language Acquisition (SLA) to frame CALL studies. The paper discusses these issues, and problems detected. [For the complete volume, "CALL and Professionalisation: Short Papers from EUROCALL 2021 (29th, Online, August 26-27, 2021)," see ED616972.]

Telecollaboration allows for students to develop foreign/second language competences linguistically, culturally, and interculturally. The use of platforms, such as WhatsApp and Zoom, is now more frequently exploited in foreign language education to ensure that a wider cross section of students, including Jamaicans, can develop global competences. This paper reports on Phase 4 of ClerKing, a six-week Franco-Jamaican telecollaborative project, which occurred between Applied Foreign Languages (AFL) students of English from University Clermont Auvergne (UCA), France, and students of various disciplines taking French courses in the Department of Modern Languages and Literatures at the University of the West Indies (UWI), Mona, Jamaica. Telecollaboration consisted in 45 participants of mixed ages and genders discussing different intercultural topics in groups. Using the exploratory approach, we seek to identify moments of Potential Learning Sequences (PLS). Preliminary findings show that PLS could be made apparent through vocabulary and syntax development, culture-specific knowledge, and negotiation of meaning. [For the complete volume, "CALL and Professionalisation: Short Papers from EUROCALL 2021 (29th, Online, August 26-27, 2021)," see ED616972.]

Computer assisted vocabulary learning, i.e. specialized terminology acquisition, is a major tool to learning Languages for Specific Purposes (LSP) necessary to students' professionalization. One current area of research is digital game-based language learning because of its motivating qualities. This paper discusses electronics students' acquisition of specific vocabulary as related to the free game-based collaborative platform Check Your Smile (CYS), which is entirely devoted to learning LSP terminology. CYS aggregates various types of games that automatically generate individualized game plays, drawing upon a collaboratively constructed multilingual dictionary. The study focuses on multiple variables including attending a selective engineering course taught in English and the language used to teach the mandatory electronics class. Empirical data shows that students having used CYS tend to obtain better vocabulary test scores than students who did not. [For the complete volume, "CALL and Professionalisation: Short Papers from EUROCALL 2021 (29th, Online, August 26-27, 2021)," see ED616972.]

This study aims to analyse the initial use of Digital Storytelling (DS) in primarily asynchronous classes in order to yield results and recommendations for future courses. All participants were students in elective English courses at a Japanese university in Spring, 2020. Due to COVID-19, the courses were redesigned and conducted remotely with the use of pre-recorded materials. Data were collected through a post-questionnaire. This short paper reports what was found from the data by analysing the questionnaire with CALL evaluation criteria developed by Jamieson, Chapelle, and Preiss (2005). From the post-questionnaire, it was revealed that the DS assignment was perceived positively to some extent in remote learning settings. However, it also highlighted the need for further in-depth technical and language support and interactive learning opportunities. [For the complete volume, "CALL and Professionalisation: Short Papers from EUROCALL 2021 (29th, Online, August 26-27, 2021)," see ED616972.]

This paper investigates the differences between Immersive Virtual Reality (IVR) and the webcam (WBC) in the context of a Spanish distance-learning course. Two specific objectives were set: (1) to determine the existence of a relationship of dependence between the device used and the oral interaction, and (2) to analyse the existence of a dependency relationship between the device utilised and the perception of copresence. To that end, online courses and semi-structured interviews were conducted. Regarding the first objective, there is a higher chance of speaking exchanges between student-tutor and tutor-student when using WBC. As for the second objective, we did not have sufficient feedback to determine whether the perception of copresence varies depending on the two profiles. However, the analysis indicates that non-verbal communication was essential for IVR volunteers to experience copresence. The conclusions suggest that the IVR could be more appropriate than WBC for socio-constructivist and communicative teaching pedagogies [For the complete volume, "CALL and Professionalisation: Short Papers from EUROCALL 2021 (29th, Online, August 26-27, 2021)," see ED616972.]

The HERO project aims to develop a training program for caregivers to be working in the elderly care sector. The program is particularly addressed to caregivers from Middle Eastern and African countries as refugees and intends to help them integrate into European society. This paper seeks to offer an overview of the project, including its objectives, underlying principles, and deliverables. The paper particularly portrays the second intellectual output (O2) of the project, namely the 'On the job' training in language and terminology curriculum, which has been developed as the end product of O2. Initially, the methodology adopted to create learning material for language learning in a specific-purpose context is analyzed. Based on this, the paper provides a description of the content development by justifying and showcasing the learning material and laying out the logic behind this, through the trainers' guide. E-learning tools have been integrated in the course material, which also justifies the methodology applied for the purpose of this project. [For the complete volume, "CALL and Professionalisation: Short Papers from EUROCALL 2021 (29th, Online, August 26-27, 2021)," see ED616972.]

With the rapid advancement of technology, education is undergoing a transformational change. Chatbots have become increasingly popular in recent years and are being utilized as teaching assistants to support teachers and students in various ways. However, little research has been done on the skills required by teachers to prepare curriculum content using chatbots. The research aims to identify the skills teachers need to prepare curriculum content with chatbots. It examines the fundamental and cognitive skills individuals need to interpret content generated by chatbots and explores the difference between self-assessment and evaluator-based assessment. Fifty-eight third-year students, pre-service teachers, in the Elementary education program attempted to write a lesson plan using ChatGPT and completed a questionnaire to assess the skills required. Their communication with the chatbot as well as their prepared lesson plans were reviewed by an evaluator who rated the skills of the participating pre-service teachers. Results indicate that preservice teachers tend to overestimate their skills required to interpret chatbot-generated content compared to the evaluator's ratings. Such discrepancies could lead to inaccurate or incomplete assessments of their skills, which could hinder their potential for growth and development. [For the full proceedings, see ED629086.]

As evidence grows supporting the importance of non-cognitive factors in learning, computer-assisted learning platforms increasingly incorporate non-academic interventions to influence student learning and learning related-behaviors. Non-cognitive interventions often attempt to influence students' mindset, motivation, or metacognitive reflection to impact learning behaviors and outcomes. In the current paper, we analyze data from five experiments, involving seven treatment conditions embedded in mastery-based learning activities hosted on a computer-assisted learning platform focused on middle school mathematics. Each treatment condition embodied a specific non-cognitive theoretical perspective. Over seven school years, 20,472 students participated in the experiments. We estimated the effects of each treatment condition on students' response time, hint usage, likelihood of mastering knowledge components, learning efficiency, and post-tests performance. Our analyses reveal a mix of both positive and negative treatment effects on student learning behaviors and performance. Few interventions impacted learning as assessed by the post-tests. These findings highlight the difficulty in positively influencing student learning behaviors and outcomes using non-cognitive interventions. [This paper was published in: "LAK23: 13th International Learning Analytics and Knowledge Conference Proceedings," March 13-17, 2023.]

This paper demonstrates how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. We examined: (1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance prediction; and (2) what types of in-game features were associated with student math knowledge scores. The results indicated that the Random Forest algorithm showed the best performance in predicting posttest math knowledge scores among the seven algorithms employed. Out of 37 features included in the model, the validity of the students' first mathematical transformation was the most predictive of their math knowledge scores. Implications for game learning analytics and supporting students' algebraic learning are discussed based on the findings.

Computer-assisted learning platforms (CALPS) increasingly include gamified elements to improve student outcomes by enhancing their engagement with content. Although evidence exists that gamified programs increase engagement and learning outcomes, there is little causal research on what programmatic mechanisms drive the effect between engagement and learning. In the following paper, we explore this relationship through a method of causal moderation known as fully latent principal stratification. Using data from a large-scale randomized control trial assessing gamified and traditional CALP systems' effects on algebraic knowledge, we estimate the impact of using the gamified CALP on students who engage with one of its key gamification elements--replaying a problem after a suboptimal attempt. The gamified CALP asks students to manipulate algebraic expressions from start to goal states and provides feedback based on the efficiency of these manipulations, allowing students to replay the problems when their efficiency can be improved. We find that the effect of gamification is greater for students with a higher propensity to replay problems. This finding suggests that gamification elements that provide students with opportunities to retry problems are driving the game's efficacy and provide evidence for a scalable mechanism of gamification that can improve students' learning. [This paper was published in: "Proceedings of the Tenth ACM Conference on Learning @ Scale (L@S '23), July 20-22, 2023, Copenhagen, Denmark," ACM, 2023, pp.164-173.]

Interactive simulations allow students to discover the underlying principles of a scientific phenomenon through their own exploration. Unfortunately, students often struggle to learn effectively in these environments. Classifying students' interaction data in the simulations based on their expected performance has the potential to enable adaptive guidance and consequently improve students' learning. Previous research in this field has mainly focused on a-posteriori analyses or investigations limited to one specific predictive model and simulation. In this paper, we investigate the quality and generalisability of models for an early prediction of conceptual understanding based on clickstream data of students across interactive simulations. We first measure the students' conceptual understanding through their in-task performance. Then, we suggest a novel type of features that, starting from clickstream data, encodes both the state of the simulation and the action performed by the student. We finally propose to feed these features into GRU-based models, with and without attention, for prediction. Experiments on two different simulations and with two different populations show that our proposed models outperform shallow learning baselines and better generalise to different learning environments and populations. The inclusion of attention into the model increases interpretability in terms of effective inquiry. The source code is available on Github. [For the full proceedings, see ED623995.]

The National Council of Teachers of Mathematics (NCTM) has been emphasizing the importance of teachers' pedagogical communication as part of mathematical teaching and learning for decades. Specifically, NCTM has provided guidance on how teachers can foster mathematical communication that positively impacts student learning. A teacher may have different academic goals towards what needs to be achieved in a classroom, which require a variety of discourse-based tools that allow students to engage fully in mathematical thinking and reasoning. Accountable or academically productive talk is one such approach for classroom discourse that may ensure that the discussions are coherent, purposeful and productive. This paper discusses the use of a transformer model for classifying classroom talk moves based on the accountable talk framework. We investigate the extent to which the classroom Accountable Talk framework can be successfully applied to one-on-one online mathematics tutoring environments. We further propose a framework adapted from Accountable Talk, but more specifically aligned to one-on-one online tutoring. The model performance for the proposed framework is evaluated and compared with a small sample of expert coding. The results obtained from the proposed framework for one-on-one tutoring are promising and improve classification performance of the talk moves for our dataset. [For the full proceedings, see ED623995.]