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Motivational research identifies utility value, or the importance of a learning task to future goals, as central to motivation to learn. This study analyzed survey data (N = 86) collected from adult literacy learners to examine their utility value of writing improvement in grammar and spelling skills, word processing skills, and planning, drafting, and revising skills. Findings revealed that participants had a high utility value of improving writing in all three skill areas and possessed a variety of underlying motivations, including obtaining further education, seeking future employment, and personal reasons. Participants' age, educational attainment, and reading levels showed relationships with utility value of improving grammar and spelling skills, and age showed an additional relationship to utility value of improving word processing skills. This work extends research on motivation in this population and supports the application of expectancy-value theory to both adult motivation and writing motivation.

Students today are often assumed to be digitally literate and prepared for college, but that is not always the case. Introductory technology courses at the college level provide students with the technology and digital skills necessary for them to succeed in college. This study, conducted at a small New England "business school" that also offers liberal arts degrees, sought to determine which digital skills most incoming first-year college students have. The study examines which digital skills and competencies students acquire before entering college, and if those skills are adequate to achieve academic success in college. Guiding the study are these research questions: (RQ1) What digital devices are students using and with what frequency? (RQ2) What digital literacy competencies (DLCs) do incoming first-year students possess? (RQ3) How do first-year students self-rank their DLCs, and how does that compare to individual task self-ranking? (RQ4) What DLCs do incoming first-year students perceive as the most important to know, and do they have those skills? Results showed that most K-12 students are learning on Macs or Chromebooks and use the Google Suite of applications. They may need to switch to Windows machines and/or Microsoft Office products upon entering college. Almost 16% reported taking no high school courses covering computer topics. Only 34% of incoming first-year college students consider themselves "tech savvy" and most rank themselves at the beginner or intermediate level on digital literacy competencies. They believe the three most important skills to know are spreadsheets, programming, and word processing.

To investigate whether a creative writing unit in upper secondary education would improve students' creative as well as argumentative text quality and to examine whether it would change students' writing behavior, we tested a creative writing unit based on encouraging writing in flow by using divergent thinking tasks. Four classes (Grade 10) participated in a switching replications design. Students received either creative writing instruction (CWI) or argumentative writing instruction (AWI). Key stroke logging software recorded students' writing processes, their Creative Self-Concept (CSC) was measured, and text quality was rated holistically. Students were positive about the design of the creative writing unit and the lessons. The effects varied per panel. The first panel showed that CWI had an effect on creative text quality compared to AWI, while AWI had no effect on argumentative text quality, compared to CWI. This pattern indicates a transfer effect of creative writing instruction on argumentative text quality. The transfer effect was moderated by CSC, with larger effects for relatively high CSC-participants. The second panel did not replicate this pattern. Instead, a crossover effect was observed of CWI in panel 1 on the effect of participating in the unit on argumentative writing in panel 2, most pronounced in high CSC-participants. Students' creative writing speed decreased in the first panel, except for students with a relatively high Creative Self-Concept, and then increased in the second panel. Our findings may guide decisions on incorporating creative writing in the curriculum.

Differentiated instruction is much demanded yet quite challenging in face of the growing student diversity in today's K-12 classrooms. One major challenge is the provision of differentiated materials to students. Automated text simplification (ATS) tools fueled by natural language processing may serve as a useful assistant for teachers. However, little is known about teachers' contextualized use of ATS over time. This case study traced two teachers' use of ATS systems over a semester. Drawing upon three semi-structured interviews and teacher-generated materials with ATS, we identified an evolving pattern of teachers' engagement with ATS systems, a progression from a blind reliance on the tool to a more critical and coordinated use of the tool over time. We further revealed that teachers' evolving understanding of DI, positioning of the role of ATS systems and human instructors, and interpretation of DI need in specific teaching situations interplayed to shape their particular ways of engagement. Overall, this study contributes to the understanding of teachers' contextualized use of ATS technology for DI. By revealing the influencing factors, the findings hold significant pedagogical implications to inform the design of ATS tools and the creation of favorable conditions to maximize the potential of ATS tools for DI and language teaching and learning in general.

With the Interactive-Constructive-Active-Passive (ICAP) framework as a foundation, author Robby Robinette presents two activities that teachers can use to incorporate collaboration into their online (and in-person) classes. The activities make use of students' prior knowledge. The author suggests sources where teachers can find reading texts that are appropriate for the activities.

Research on academic integrity used to focus more on student character and behaviour. Now this research includes wider viewing of this issue as a current teaching and learning challenge which requires pedagogical intervention. It is now the responsibility of staff and institutions to treat the creation of a learning environment supporting academic integrity as a teaching and learning priority. Plagiarism by simply copying other people's work is a well-known misconduct which undermines academic integrity; moreover, technological developments have evolved plagiarism to include the generation and copying of computer-generated text. Automated paraphrasing tool (APT) websites have become increasingly common, offering students machine-generated rephrased text that students input from their own or others' writing. These developments present a creeping erosion of academic integrity under the guise of legitimate academic assistance. This also has implications for arrival of large language model (LLM) generative AI tools. In accessing these sites, students must discern what is a legitimate use of the tool and what may constitute breaching academic integrity. This study critically analysed the text from five online paraphrasing websites to examine the discourses used to legitimise and encourage APT use in both appropriate and inappropriate ways. We conceptualised these competing discourses using Sheep and Wolf metaphors. In addition, we offer a metaphor of the Educator as a Shepherd to become aware of APT website claims and assist students to develop critical language awareness when exposed to these sites. Educators can assist students with this through knowledge of how these sites use language to entice users to circumvent learning.

In recent years, higher education (HE) globally has witnessed extensive adoption of technology, particularly in teaching and research. The emergence of generative Artificial Intelligence (GenAI) further accelerates this trend. However, the increasing sophistication of GenAI tools has raised concerns about their potential to automate teaching and research processes. Despite widespread research on GenAI in various fields, there is a lack of multicultural perspectives on its impact and concerns in HE. This study addresses this gap by examining the usage, benefits, and concerns of GenAI in higher education from a multicultural standpoint. We employed an online survey that collected responses from 1217 participants across 76 countries, encompassing a broad range of gender categories, academic disciplines, geographical locations, and cultural orientations. Our findings revealed a high level of awareness and familiarity with GenAI tools among respondents. A significant portion had prior experience and expressed the intention to continue using these tools, primarily for information retrieval and text paraphrasing. The study emphasizes the importance of GenAI integration in higher education, highlighting both its potential benefits and concerns. Notably, there is a strong correlation between cultural dimensions and respondents' views on the benefits and concerns related to GenAI, including its potential as academic dishonesty and the need for ethical guidelines. We, therefore, argued that responsible use of GenAI tools can enhance learning processes, but addressing concerns may require robust policies that are responsive to cultural expectations. We discussed the findings and offered recommendations for researchers, educators, and policymakers, aiming to promote the ethical and effective integration of GenAI tools in higher education.

This study compares the effects of two resources, a paper rubric (CR) or the comment bubbles from a word processor (CCB), to support peer co-evaluation of expository texts in primary education. A total of 57 students wrote a text which, after a peer co-evaluation process, was rewritten. To analyze the improvements in the texts, we used a rubric that was similar to the one in the first condition. The messages and suggestions for improvement were quantified and classified according to their range, evaluative content, and rhetorical content. Lastly, the incorporation of these suggestions in the final version of the expository text was analyzed. The results showed that the evaluative comments focused mainly on pointing out, rating, or simply correcting errors. However, hardly any justification was given for such corrections, nor were there any questions or improvement alternatives recorded for other shortcomings or non-error content. The students who co-evaluated each other with a rubric wrote more comments, addressing the different rhetorical components in a balanced way, even though these comments were written in a generic way. This might be why many of them were not incorporated in the second version of the texts, where a significant improvement could be noticed, but only in the conclusion section. In contrast, the comment bubbles recorded much more specific suggestions for correction. Although there was a slightly higher percentage of modifications in the second version of those texts, it was not enough to indicate a significant improvement in quality compared to the first version.

Text-matching software (TMS) is a standard part of efforts to prevent and detect plagiarism in upper secondary and higher education. While there are many studies on the potential benefits of using this technology, few studies look into potential unintended side effects. These side effects include students worrying about being accused of plagiarism due to TMS output, even though they did not intentionally plagiarise. Although such worries are frequently mentioned in the literature, little is known about how prevalent they are, why they occur and how students react to them. This paper aims to fill this knowledge gap. The data for the study comprise 36 interviews with upper secondary and Bachelor students from three European countries combined with survey data from 3,424 students from seven European countries representing a broad range of disciplines. The study found that a substantial proportion of the two groups of students -- 47% of upper secondary and 55% of Bachelor students -- had experienced TMS-related worries during their current studies. Furthermore, there were substantial differences across countries. Students worry partly because they have a poor understanding of how TMS is used in their institution, and partly because they know that plagiarism is taken very seriously. The study shows that TMS-related worries can lead students to become very focused on not being caught plagiarising, to such an extent that some adopt citation practices that they believe are suboptimal. The paper concludes that institutions using TMS should always combine it with training for students and teachers. Students should be clearly informed about how TMS is used and should develop an understanding of plagiarism and good citation practice that goes beyond the narrow focus on any overlap between texts elicited by the software.

In response to COVID-19, universities worldwide experienced drastic and sudden changes including the need to shift to online teaching and assessment. Following previous research suggesting that individual differences in typing skills could influence text quantity and quality, we investigated whether university students' typing speed is related to their performance in an online written exam, considering that low typing skills could potentially be disadvantageous. To this end, first-year university students participated in a copy-typing task immediately after completing a graded online exam. Results show a trend toward a triangular relationship between typing speed, text length and exam performance. Despite coefficients being small, this approach allows unique insights into externally valid data of university students' typed free text production in an authentic online exam situation. Our findings emphasize the need for more research into this highly variable skill in order to understand and minimize unwanted interindividual differences that could possibly influence exam outcomes.

Based on an analysis of three literacy events in nursery schools, this article focuses on how literacy forms part of children's social practices and co-creates the language environment in the nursery and how place, affect and materiality play a key role in children's multimodal and embodied meaning-making around literacy. The analysis is based on ethnographic fieldwork in two nursery schools, in which we followed different children through their days in order to explore how they used language in different contexts, what characterised their language practices and what appeared to encourage and constrain their desire to express themselves. It shows how the written word means much more to children than knowledge about the structure of books and identification of letters and how children draw on their own experience and include the place and the available materials in their joint meaning-making processes. Against this background, we argue for the need for a reconceptualisation of what literacy is and can be in a nursery school context and for a discussion of the implications of this for teaching literacy.

Students must be able to produce legible and fluent text when completing classwork and for exam purposes. Some students, however, present with handwriting difficulties in secondary school. When these are significant, intervention may be necessary or alternatives to handwriting may be offered (e.g. use of a word processor). Little is known about current practice of supporting secondary students with handwriting difficulties in England and how recommendations are made to transition to typing. Semi-structured interviews were conducted with 13 practitioners with a responsibility for supporting students with handwriting difficulties. Two themes were identified. The first theme, "doing the right thing," illustrated the tension between practitioners' commitment to supporting students with handwriting difficulties and their uncertainty around what is the "right" approach. The second theme, "influencing practice," described the contextual factors (student and family, school environment and national context) that impact on practitioners' practice and their decision to transition from handwriting to typing. Findings highlight the complexities of supporting this group of students and an urgent need for guidance at a national level to assist best practice. Implications for practice are discussed. Further research examining the effectiveness of handwriting interventions with secondary students and the optimum time to start typing is warranted.

Background: Word-to-text integration (WTI) can be challenging for second-language (L2) learners, although it can positively contribute to reading comprehension. The present study examined the role of WTI, after controlling for decoding, vocabulary and morphosyntactic awareness, in predicting English as an L2 reading comprehension development in 441 Dutch seventh-grade students. Methods: At the beginning (Time 1 [T1]) and the end (Time 2 [T2]) of the school year, students were tested on their English decoding, vocabulary, morphological and syntactic awareness and reading comprehension with paper-and-pencil tasks and on WTI with a self-paced reading task with reading times being compared on passages with unknown versus known words and passages with and without anomalies. Results: Mediation analyses showed small indirect effects of processing argument overlap and anomalies on T2 reading comprehension, via T1 reading comprehension. Conclusions: WTI explained unique variance in reading comprehension at T2 via reading comprehension at T1, suggesting that it moderately impacts initial stages of reading comprehension in English as a second language (ESL).

Background: Recent research has documented individual differences in the reading profiles of skilled native English readers using a behavioural marker of holistic visual word processing (orientation sensitivity). A more holistic word reading profile is associated with a weaker correlation with phonological decoding for word identification. Interestingly, that is different from typical patterns in skilled reading in English. The current study aimed to further assess the underlying distribution of orientation sensitivity as a continuous measure in an unrestricted undergraduate population and to extend past findings to understand the role of phonological decoding in reading comprehension as a function of orientation sensitivity. Methods: A group of 137 SUNY New Paltz undergraduates completed an orientation sensitivity test to assess the overarching distribution. A subset of 55 SUNY New Paltz undergraduates completed additional reading-related tests (phonological decoding and reading comprehension) on an online platform (findingfive.com). The relationship between orientation sensitivity and reliance on phonological decoding on reading comprehension was assessed using regression. Results: Results found that the distribution of orientation sensitivity was not normal and skews to the right, but is not bimodal, thus warranting the use of regression instead of group statistics. Lastly, those with relatively greater orientation sensitivity had a weaker relationship between measures of phonological decoding and a reading comprehension measure, as predicted. Conclusions: The results extended the finding of differences in reliance on phonological decoding to reading comprehension as a function of orientation sensitivity. These results help refine our understanding of orientation sensitive readers and potential alternative route to successful reading found in the general population.

Integrated writing assessments are tasks that require students to construct an essay using evidence from source texts. Topic models are statistical models used to analyze text. This study analyzes two integrated writing tasks from students in grades 6 (N=1,250) and 8 (N=1,250) using topic models. Independent evaluations of the essays were also conducted to help generalize the results across the two grades and better understand students' underlying writing techniques. Four main categories were identified: (1) use of words that appeared in the prompt, (2) words that appeared in the source texts, (3) words that reflected inference, and (4) words that reflected integration. Higher-scoring students used words that reflect inference and integration of source text more often than lower-performing students.

Student opinions for a course are important to educators and administrators, regardless of the type of the course or the institution. Reading and manually analyzing open-ended feedback becomes infeasible for massive volumes of comments at institution level or online forums. In this paper, we collected and pre-processed a large number of course reviews publicly available online. We applied machine learning techniques with the goal to gain insight into student sentiments and topics. Specifically, we utilized current Natural Language Processing (NLP) techniques, such as word embeddings and deep neural networks, and state-of-the-art BERT (Bidirectional Encoder Representations from Transformers), RoBERTa (Robustly optimized BERT approach) and XLNet (Generalized Auto-regression Pre-training). We performed extensive experimentation to compare these techniques versus traditional approaches. This comparative study demonstrates how to apply modern machine learning approaches for sentiment polarity extraction and topic-based classification utilizing course feedback. For sentiment polarity, the top model was RoBERTa with 95.5% accuracy and 84.7% F1-macro, while for topic classification, an SVM (Support Vector Machine) was the top classifier with 79.8% accuracy and 80.6% F1-macro. We also provided an in-depth exploration of the effect of certain hyperparameters on the model performance and discussed our observations. These findings can be used by institutions and course providers as a guide for analyzing their own course feedback using NLP models towards self-evaluation and improvement.

Recurrence quantification analysis (RQA) is a time-series analysis method that uses autocorrelation properties of typing data to detect regularities within the writing process. The following paper first gives a detailed introduction to RQA and its application to time series data. We then apply RQA to keystroke logging data of first and foreign language writing to illustrate how outcome measures of RQA can be understood as skill-driven constraints on keyboard typing performance. Forty native German students performed two prompted writing assignments, one in German and one in English, a standardized copy task, and a standardized English placement test. We assumed more fluent and skilled writing to reveal more structured typing time series patterns. Accordingly, we expected writing in a well-mastered first language to coincide with higher values in relevant RQA measures as compared to writing in a foreign language. Results of mixed model ANOVAs confirmed our hypothesis. We further observed that RQA measures tend to be higher, thus indicating more structured data, whenever parameters of pause, burst, and revision analyses indicate more fluent writing. Multiple regression analyses revealed that, in addition to typing skills, language proficiency significantly predicts outcomes of RQA. Thus, the present data emphasize RQA being a valuable resource for studying time series data that yields meaningful information about the effort a writer must exert during text production.

Revision plays an important role in writing, and as revisions break down the linearity of the writing process, they are crucial in describing writing process dynamics. Keystroke logging and analysis have been used to identify revisions made during writing. Previous approaches include the manual annotation of revisions, building nonlinear S-notations, and the automated extraction of backspace keypresses. However, these approaches are time-intensive, vulnerable to construct, or restricted. Therefore, this article presents a computational approach to the automatic extraction of full revision events from keystroke logs, including both insertions and deletions, as well as the characters typed to replace the deleted text. Within this approach, revision candidates are first automatically extracted, which allows for a simplified manual annotation of revision events. Second, machine learning is used to automatically detect revision events. For this, 7120 revision events were manually annotated in a dataset of keystrokes obtained from 65 students conducting a writing task. The results showed that revision events could be automatically predicted with a relatively high accuracy. In addition, a case study proved that this approach could be easily applied to a new dataset. To conclude, computational approaches can be beneficial in providing automated insights into revisions in writing.

This paper argues that traditional threshold-based approaches to the analysis of pauses in writing fail to capture the complexity of the cognitive processes involved in text production. It proposes that, to capture these processes, pause analysis should focus on the transition times between linearly produced units of text. Following a review of some of the problematic features of traditional pause analysis, the paper is divided into two sections. These are designed to demonstrate: (1) how to isolate relevant transitions within a text and calculate their durations; and (2) the use of mixture modelling to identify structure within the distributions of pauses at different locations. The paper uses a set of keystroke logs collected from 32 university students writing argumentative texts about current affairs topics to demonstrate these methods. In the first section, it defines how pauses are calculated using a reproducible framework, explains the distinction between linear and non-linear text transitions, and explains how relevant sections of text are identified. It provides Excel scripts for automatically identifying relevant pauses and calculating their duration. The second section applies mixture modelling to linear transitions at sentence, sub sentence, between-word and within-word boundaries for each participant. It concludes that these transitions cannot be characterised by a single distribution of "cognitive" pauses. It proposes, further, that transitions between words should be characterised by a three-component distribution reflecting lexical, supra-lexical and reflective processes, while transitions at other text locations can be modelled by two-component distributions distinguishing between fluent and less fluent or more reflective processing. The paper concludes by recommending that, rather than imposing fixed thresholds to distinguish processes, researchers should instead impose a common set of theoretically informed distributions on the data and estimate how the parameters of these distributions vary for different individuals and under different conditions.

Artificial intelligence tools have presented many challenges and opportunities to transform teaching and learning on college campuses. These changes are significant enough to require colleges to take action to create a framework by which faculty and students can navigate the proper usage of these tools. Rather than working to create entirely new policies strictly for addressing these new technologies, they should instead edit their existing academic integrity and intellectual property statements to incorporate explicit mentions of artificial intelligence.

In this article, a dialogue text feature extraction model based on big data and machine learning is constructed, which transforms the high-dimensional space of text features into the low-dimensional space that is easy to process, so that the best feature words can be selected to represent the document set. Tests show that in most cases, the classification accuracy of this model is higher than 88%, and the recall rate is higher than 85%, thus achieving the goal of higher classification accuracy with less computation. When extracting the features of dialogue texts, there is no need for preprocessing, just count the data such as lexical composition, sentence length and sentence-to-sentence relationship of the target text, and make linear analysis to obtain key indicators and weights. Based on this, the classification model can achieve good results, thus effectively reducing the workload and computation of text classification.

This study investigates the efficacy of six major Generative AI (GenAI) text detectors when confronted with machine-generated content modified to evade detection (n = 805). We compare these detectors to assess their reliability in identifying AI-generated text in educational settings, where they are increasingly used to address academic integrity concerns. Results show significant reductions in detector accuracy (17.4%) when faced with simple techniques to manipulate the AI generated content. The varying performances of GenAI tools and detectors indicate they cannot currently be recommended for determining academic integrity violations due to accuracy limitations and the potential for false accusation which undermines inclusive and fair assessment practices. However, these tools may support learning and academic integrity when used non-punitively. This study aims to guide educators and institutions in the critical implementation of AI text detectors in higher education, highlighting the importance of exploring alternatives to maintain inclusivity in the face of emerging technologies.

In using software to write a scientific, technical, or other scholarly document, authors have essentially two options. They can either write it in a 'what you see is what you get' (WYSIWYG) editor such as a word processor, or write it in a text editor using a markup language such as HTML, LATEX, Markdown, or AsciiDoc. This paper gives an overview of the latter approach, focusing on both the non-visual accessibility of the writing process, and that of the documents produced. Currently popular markup languages and established tools associated with them are introduced. Support for mathematical notation is considered. In addition, domain-specific programming languages for constructing various types of diagrams can be well integrated into the document production process. These languages offer interesting potential to facilitate the non-visual creation of graphical content, while raising insufficiently explored research questions. The flexibility with which documents written in current markup languages can be converted to different output formats is emphasized. These formats include HTML, EPUB, and PDF, as well as file formats used by contemporary word processors. Such conversion facilities can serve as means of enhancing the accessibility of a document both for the author (during the editing and proofreading process) and for those among the document's recipients who use assistive technologies, such as screen readers and screen magnifiers. Current developments associated with markup languages and the accessibility of scientific or technical documents are described. The paper concludes with general commentary, together with a summary of opportunities for further research and software development.

It is unknown whether and to what extent cognitive individual differences may play different roles in paper versus computer-based second language (L2) writing. This exploratory study is a first attempt to explore this issue, focusing on the effects of working memory and language aptitude on the quality of paper versus computer-based L2 writing performance. Forty-two Spanish learners of L2 English performed a problem-solving task either digitally or on paper, took a working memory n-back test, and completed LLAMA tests to measure language aptitude. The quality of their L2 written texts was assessed in terms of complexity, accuracy and fluency (CAF) measures. The results indicated that the role of cognitive individual differences may vary depending on the writing environment.

This study compared the effects of computer-mediated (CM) versus pen-and-paper (P&P) writing on written accuracy and feedback processing in tasks written and rewritten collaboratively following a pedagogical treatment in two intact authentic classrooms. The study involved 32 secondary education low-proficiency English-as-a-foreign-language (EFL) learners writing two descriptive texts collaboratively and receiving in-class training in the identification and correction of grammatical, lexical, and mechanical errors. Participants were provided with unfocused direct error correction (EC). Error logs were used to facilitate noticing of teacher corrections (i.e., feedback processing). Dyads were required to rewrite their texts for evidence of feedback uptake. Results indicate that writing collaboratively on the computer with the availability of the Internet contributes to increased grammatical and lexical accuracy. No differences were found between writing environments regarding feedback processing or accuracy of rewritten texts.

The aim of this study is to determine the metaphor perceptions of Generation Z teacher candidates towards handwriting and typing. Based on the metaphors obtained, elective courses related to handwriting may be included in undergraduate programs according to their point of view on handwriting. Many researches are carried out on the area created by the change that comes with the use of new technology. However, it is still necessary to ask new questions and seek answers. Therefore, in this study, according to the medium in which it is presented, whether in print or digital, how the nature of the content of the article changes according to the medium; what are the consequences of the superficialization of the content in terms of mental processes and what are the pre-service teachers' perspectives on handwriting. Study group of this research consists of 70 students among the Teacher Candidates in Istanbul in the fall semester of the 2020-2021 school year. For the data collection, a form with incomplete sentences such as "Handwriting is like... Because…" and "Keyboarding (typing) is like… Because…" was used to allow students to write down metaphors they attribute to "writing". Generation Z Teacher Candidates produced metaphors in the category of handwriting respectively the life (27.1%), thought and feelings (20%) attention and production (15.7%), skill (15.7%), functional (12.9%) and share/transfer (8.6%). Teacher Candidates produced metaphors in the category of keyboarding (typing) high level attention/production (24.3%), superficiality/forgery (21.4%), easy/effortless (17.1%), thought and feelings (12.9%), sound (10%), skill (8.6%) and future (5.7%). Teacher Candidates should provide content and environments that will increase the longing for handwriting in their students to create awareness of writing and make them feel the need for writing. The determination of the meanings attributed by the Generation Z Teacher Candidates to traditional writing and typing with keys, and the perspective of Teacher Candidates on this subject were discussed.

Writing is usually the last skill to be touched upon in language classrooms, and more so, in the EFL or ESL classroom. Even so, postponing or the tendency to avoid the writing task is a common hindrance created by the learners, but is definitely one that retards the learning of the skill. The current study aimed to examine the efficacy of working collaboratively on digital platforms to enhance learners' engagement with writing in addition to boosting their writing proficiency. The participants in this study are forty-eight advanced level EFL learners at Qassim University. The study used both questionnaire and pre and post tests to collect data from he sample. Intervention lasted eight weeks and comparative results were computed using descriptive statistics in the standardised IELTS pre and post-test components for writing proficiency. Results showed a raise of between 47.36%-19.14 in group output from the first to the last week of the intervention. The paired sample t-value at 3.0402 suggests that the results support the null hypothesis that Collaborative Writing on a Digital Platform (CWDP) helps enhance writing performance in EFL learners since the difference between pre and post tests is statistically significant. Results obtained from a perceptions questionnaire evaluating learners' attitudes to CWDP clearly indicate a decided preference for the approach, both for its collaborative and tech value. The study concludes that collaborative writing in digital spaces contributes positively to enhancing Saudi university EFL learners' global writing proficiency and should be incorporated into the regular curriculum.

Learning Management Systems (LSM) have been adopted to provide interaction between instructors and students in online learning courses. In these environments, large volumes of messages are exchanged, making it difficult for the participants to follow all the discussions. When messages are ignored, students' opportunities to effectively construct knowledge through online discussions are reduced. In this context, this paper proposes a method for mining the content of messages written in Brazilian Portuguese to enhance students and instructors' interactions in online discussion forums. Four different automatic methods were developed, one for each of the following four dimensions of the originality and collaboration processes: (i) Semantic textual similarity to measure originality; (ii) Expressing appreciation towards other participants; (iii) Recognizing group presence; (iv) Sharing information and resources; (v) Soliciting feedback/Answering questions. The use of the methods for analyzing online discussions forums was validated in a case study conducted in a real course. A discussion forum tool was developed to provide feedback for students and instructors about the originality and collaboration level during online discussions. Results showed the potential of the proposal in promoting students' collaboration, enhancing interaction and reducing plagiarism in discussion forums.

"Biometrics" are physical or behavioral human characteristics that can be used to identify a person. It is widely known that keystroke or typing dynamics for short, fixed texts (e.g., passwords) could serve as a behavioral biometric. In this study, we investigate whether keystroke data from essay responses can lead to a reliable biometric measure, with implications for test security and the monitoring of writing fluency and style changes. Based on keystroke data collected from a high-stakes writing testing setting, we established a preliminary biometric benchmark for detecting test-taker identity by using features extracted from their writing process logs. We report a benchmark keystroke biometric accuracy of equal error rate of 4.7% for identifying same versus different individuals on an essay task. In particular, we show that the inclusion of writing process features (e.g., features designed to describe the writing process) in addition to the widely used typing-timing features (e.g., features based on the time intervals between two-letter key sequences) improves the accuracy of the keystroke biometrics. The proposed keystroke biometrics can have important implications for the writing assessments administered through the remotely proctored tests that have been widely adopted during the COVID pandemic.

Comprehension of stories requires readers to take the perspective of the story characters and imagine or feel their cognitive and affective states. The study investigated how variations in emotional valence within a literary text affected readers' global text processing, as reflected in their eye movements during the first and second-pass reading, and their memory for text. Processes of reading were also examined in relation to readers' dispositional empathy. Undergraduate students (N = 42) were assigned to an emotionally negative or neutral reading condition. They read a natural text passage from a suspense story while their ocular behavior was registered. After reading, they responded to multiple-choice questions assessing their memory of the text. Results revealed longer first-pass fixation times for content evoking negative emotions than for neutral content, which could be suggestive of a more analytical processing of the former. These effects were however local and did not impact the processing of the text at global level. Memory for the emotionally negative content was more accurate than memory for the neutral content. Dispositional empathy did not contribute to reading processes and outcome. Findings are discussed against the mixed results in the current literature and practical implications are also outlined.

Many college students prefer to type their lecture notes rather than write them by hand. As a result, the number of experimental and quasi-experimental studies comparing these two note-taking mediums has flourished over the past decade. The present meta-analytic research sought to uncover trends in the existing studies comparing achievement and note-taking outcomes among college students. Results from 24 separate studies across 21 articles revealed that taking and reviewing handwritten notes leads to higher achievement (Hedges' g = 0.248; p < 0.001), even though typing notes benefits note-taking volume (Hedges' g = 0.919; p < 0.001), among college students. Furthermore, our binomial effect size display shows that taking handwritten lecture notes is expected to produce higher course grades than typing notes among college students. We conclude that handwritten notes are more useful for studying and committing to memory than typed notes, ultimately contributing to higher achievement for college students.

The study aims to identify the effect of using word processor in teaching writing skill among secondary students in private schools in Jordan, clear out the differences in writing skill between the control group taught in the ordinary method and the experimental group taught using word processor. The study follows the descriptive and experimental approach to identify the effect of using word processor in teaching writing skills among secondary students in schools in Jordan. The study sample selected in random way consisted of 30 in Al-Jubaiha secondary school in the second semester (2018/2019). The study found that there are significant positive differences in the achievement of the students (experimental group) in writing skill as a result of using word processor in their teaching. The study also found that there are significant positive differences in the achievement of students (experimental group) in spelling and grammar because of the use of word processor in their teaching. This indicates the effectiveness of the word processor for the ninth grade students in writing skills. In the light of the results, the study recommends the use of word processor for teaching because of its effect on the achievement of the ninth grade students in writing skill.

Digital competence is undoubtedly one of the key skills that teaching staff should possess. Currently, there are many theoretical frameworks and ways to measure skills and knowledge related to the use of information and communication technologies (ICT). This article is an attempt to show the real and declared level of digital skills among future teaching staff. The research was conducted in Poland among 128 students of pedagogical faculties (first-year undergraduate studies). The research used a triangulation of research methods and techniques: diagnostic survey and competency tests related to the use of word processors and spreadsheets, and the level of knowledge about the use of ICT. Competency tests were in accordance with the European Computer Skills Certificate (ECDL) standard. The collected data showed the following: (1) more than half of the students rate their own skills in the use of word processors and spreadsheets, and their overall theoretical knowledge as high or very high; (2) in the case of the real assessment of digital competence, only less than 20% reached the passing threshold in the areas of word processors and theoretical knowledge, with only 1.6% passing in the area of spreadsheets; (3) the declared and actual levels of digital competence were moderately related in the surveyed group; and (4) attitudes towards new media, self-assessment of digital skills, and previous learning experience in handling ICT are not predictive factors for ECDL test results.

The authors in this study used a pre-posttest experimental design with random assignment to treatment or control group to assess the use of an electronic editing cognitive strategy. The participants were 16 college students with intellectual and developmental disabilities enrolled in a 2-year postsecondary program at a Midwestern institute of higher education. Students who were taught the strategy received eight 50-minute lessons once a week for eight weeks. Each strategy lesson was driven by the strategy mnemonic and incorporated an explicit instruction format with modeling, guided practice with feedback, and independent practice. Strategy instruction included students using desktop PCs and Microsoft Word to identify and correct editing errors in electronic passages. Posttests revealed a significant difference in favor of the treatment group for total editing errors corrected and specific error types corrected for spelling, punctuation, and substance. No significant difference was found for overall appearance and capitalization errors. Two weeks following posttest, a maintenance probe revealed that students in the treatment group corrected a significantly higher number of editing errors than those in the control group.

Mobile-learning (m-learning), or mobile-assisted language learning (MALL), has been the object of a great deal of research over the last twenty years. However, empirical work in this area has largely failed to produce generalizable conclusions due to variation in methodology, target feature, and task-type (Burston, 2014, 2015). As schools in Japan begin to join the growing number of classrooms worldwide using mobile-based assignments, this study examined how Japanese EFL students' writing task production differed depending on writing medium (i.e., handwritten on paper vs. tapped on a smartphone). Writing samples were collected from N = 1,449 participants, divided into smartphone- or paper-based groups, across a spectrum of English proficiencies. Handwritten submissions were found to be significantly longer than those composed on a smartphone (p < 0.001, d = 0.54), with differences being more pronounced for learners of higher proficiency than lower ones. Significance and effect sizes steadily dropped from p < 0.001, d = 0.66 for advanced learners to p = 0.168, d = 0.38 for beginners. These results indicate that care must be taken in designing m-learning activities, and that students must be given adequate training in smartphone-input skills (i.e., tapping) and time to acclimate before using such tasks for high-stakes assessments.

This intervention study aimed to test the effect of writing process feedback. Sixty-five Grade 10 students received a personal report based on keystroke logging data, including information on several writing process aspects. Participants compared their writing process to exemplar processes of equally scoring (position-setting condition) or higher-scoring students (feed-forward condition). The effect of the feedback on writing performance and process was compared to a national baseline study. Results showed that feed-forward process feedback had an effect on text quality comparable to one grade of regular schooling. The feedback had an effect on production, pausing, revision, and source use, which indicates that it supported participants in self-regulating their writing process. Additionally, we explored the students' perception of the feedback to get an insight into its strengths and weaknesses. This study shows the potential of writing process feedback and discusses pedagogical implications and options for future research.

Despite the solid evidence that online collaborative writing (CW) tasks benefit language learning, little is known about whether the computer-mediated communication (CMC) modality may impact the potential of online CW tasks in foreign language classrooms. This study examined the effect of task modality on the utility of CW tasks in language classrooms. Fourteen Chinese as a foreign language (CFL) learners completed Google Docs-based CW tasks in two modalities: A synchronous CMC modality entailing video-chatting in Zoom and an asynchronous CMC modality where learners interacted in Google Docs with delayed time. Through analyzing multiple data sources (i.e., peer interaction, written products, editing logs, interviews), we found that, while CMC modality did not impact writing performance, CFL learners had more language learning opportunities and more positive learning experiences in the synchronous mode than in the asynchronous one. The findings revealed multiple challenges that require attention when implementing asynchronous CW tasks in teaching.

This study explored second language (L2) reading and recall processes under different reading purposes, as reflected in their eye-movements during reading, keystrokes produced from summary writing, and stimulated recall comments. Seventy-two Korean undergraduate students read an English essay for different purposes, i.e., reading to extract the gist quickly (i.e., reading-to-skim) versus reading to prepare for a presentation (i.e., reading-to-learn), and wrote an unannounced summary of the essay. A subgroup of participants further produced stimulated recalls prompted by their own eye-movements and keystrokes. The results revealed that reading-to-skim led participants to engage in uninterrupted global text processing as manifested in significantly longer forward saccades and regressions. Those under the reading-to-learn condition, in contrast, showed significantly shorter eye-movements accompanied by constant pauses for local processing, while staying substantially longer on the essay. Reading-to-learn further resulted in more frequent pauses and revisions in the summary writing process, recalling a greater number of idea units from the essay. The findings of this study indicate that L2 learners prioritize distinct aspects of text processing depending on the reading purpose, which affects both reading and recall processes.

Reflective writing is part of many higher education courses across the globe. It is often considered a challenging task for students as it requires self-regulated learning skills to appropriately plan, timely engage and deeply reflect on learning experiences. Despite an advance in writing analytics and the pervasiveness of human feedback aimed to support student reflections, little is known about how to integrate feedback from humans and analytics to improve students' learning engagement and performance in reflective writing tasks. This study proposes a personalised behavioural feedback intervention based on students' writing engagement analytics utilising time-series analysis of digital traces from a ubiquitous online word processing platform. In a semester-long experimental study involving 81 postgraduate students, its impact on learning engagement and performance was studied. The results showed that the intervention cohort engaged statistically significantly more in their reflective writing task after receiving the combined feedback compared to the control cohort which only received human feedback on their reflective writing content. Further analyses revealed that the intervention cohort reflected more regularly at the weekly level, the regularity of weekly reflection led to better performance grades, and the impact on students with low self-regulated learning skills was higher. This study emphasizes the powerful benefits of implementing combined feedback approaches in which the strengths of analytics and human feedback are synthesized to improve student engagement and performance. Further research should explore the long-term sustainability of the observed effects and their validity in other contexts.

Over the past few years, many studies have examined the cognitive processes of students when translating texts from one language to another. However, little is known about the cognitive processes of Arab translators when translating texts from their heritage language into English. This study aims to track the cognitive processes of students as indicated by their pauses when translating two texts from Arabic into English, and vice versa. To this end, 26 Arab native students were asked to translate medical text from English into Arabic and a literary text from Arabic into English. Data on these students' behaviour were collected using a keystroke logging programme Inputlog.07, a screen recording software and a stimulated recall interview. Results from quantitative data suggest that these students paused longer at word boundaries than between sentences, and their pauses within-words were significantly shorter when translating English into Arabic, indicating that their main concerns are on the low-cognitive level such as lexis, grammar, and spelling errors. Meanwhile, results from qualitative data suggest that these students pause when facing difficulties in understanding English text, were striving to accommodate the equivalent terms in the foreign language, and were struggling with their spelling when translating Arabic into English.

Recent technology advances have enabled the collection of keystroke logs during writing, a non-intrusive approach to collecting writing process data that could provide insights into writers' editing and revising behaviors in the writing process. Using keystroke logs from 761 middle school students in the US, this study investigated the association between the writers' editing and revising behaviors, especially in-text editing and jump editing, and their scores and gender. The results showed different writing behavior patterns for participants of different ability and gender. The research findings on the writing processes went beyond character- and word-level activities and shed light on writers' revising behaviors and related writing evaluating skills, which can potentially be used for automated writing interventions.

In Temasek Polytechnic, Singapore, several AI chatbots acting as digital teaching assistants were trialed between July 2021 and August 2022. As these were developed for different purposes, it is important to learn if these AI chatbots help achieve the desired learning outcomes. This paper focuses on lessons learnt from three chatbots designed for different learning experiences: the independent learning of EXCEL, the correction of errors in the application of APA citation style, and the provision of supplementary theoretical support for software usage for Social Media Analytics. The research team studied the students' reaction to these educational chatbots, their motivation to use them, as well as the efficacy of the chatbot features to support specific purposes. This paper offers a design model that describes the three-stage approach for learning with an AI chatbot, with examples elucidating them. These sequential stages are foundational in the chatbot design to provide focused, personalised, student-controlled online learning environment. The application of this model is detailed in a fourth AI chatbot designed for the subject, Airline Management.

Texts used in L2 classrooms have traditionally been simplified manually, but recent technological advances allow us to investigate whether automatic text simplification (ATS) software can help L2 learners comprehend texts in second and foreign languages. Participants were divided into low and high L2 reading proficiency groups and assigned to read either the authentic or automatically simplified version of a text and completed a free recall task and MC comprehension test. The results did not show any significant correlations among the variables of topic knowledge, topic interest, and MC comprehension, but there were correlations among L2 reading comprehension, MC comprehension, and free recall results. Results also showed that the automatically simplified text facilitated the comprehension of the more proficient readers but not the less proficient readers according to their performance on the free recall assessment. Implications are that L2 teachers cannot blindly use whatever text they want with ATS, and ATS software designers may need to reconsider the current conservative approach to simplification that many ATS tools use.

This paper contemplates the concept of "typographical advocacy," defined here as a variety of activities, strategies, and policies designed to increase or enhance language support in computing systems, facilitating typing and displaying texts in local languages. Focusing on the cases of Spanish and Paraguayan Guarani, the paper traces some existing efforts in the domain of typographical advocacy and strives to explain their dynamics. An attempt is made to examine both situations in which typographical advocacy is visible and explicit (as in the case of Spanish) and cases in which advocacy seems negligible (as in the case of Guarani). A wide range of enabling and hindering factors are examined, such as the relations between tech companies, nation-state institutions, consumers, and the habitus created by the use of technology. Through these examples, the rationale for advocacy is explored as well as alternative courses of action in cases where advocacy is not desired or fails to achieve its goals. A case will be made for raising the awareness of typographical issues in language planning and policy (LPP) both as part of broader multilingual awareness and as a tool for solving practical language problems in times of increased dependency on computing and mobile devices.