Enhancing self‐directed learning and Python mastery through integration of a large language model and learning analytics dashboard

Background: The COVID-19 pandemic led to significant changes in nursing education; however, their impact on competencies and self-directed learning (SDL) skills achieved at the point of graduation has been limitedly investigated.Aims: To compare the perceived SDL skills and competencies at the time of graduation between pre- and postpandemic graduates; and to assess correlations, if any, between the SDL skills and competencies in both groups.Design: A repeated cross-sectional study design following the Strengthening of the Reporting of Observational Studies in Epidemiology checklist.Methods: All 2019 (prepandemic) and 2023 (postpandemic group) new graduates from two Italian Universities and willing to participate were included. The Self-Rating Scale of SDL (SRSSDLITA) and the Nurse Competence Scale (NCS) were administered. Descriptive and inferential statistics were used.Results: Postpandemic graduates reported slightly lower SDL scores (pre- 4.27 vs. postpandemic 4.18 out of 5, p = 0.030), with significant declines in “Awareness” (p = 0.005), “Learning Strategies” (p < 0.001), and “Interpersonal Skills” factors (p = 0.007). Perceived overall competence as measured with the NCS was higher in the postpandemic group (pre- 68.01 out of 100 vs. post- 71.08, p = 0.020), with significant gains in “Helping Role” (p = 0.005), “Teaching-Coaching” (p < 0.001), and “Ensuring Quality” dimensions (p < 0.001). Correlations between SDL skills and competencies perceived were weaker in the postpandemic group.Conclusions: The perceived competencies have improved while the SDL skills slightly declined in the postpandemic group, suggesting new needs of graduates in the transition to their professional role. The weak correlation between SDL skills and competencies in the postpandemic group underlines the importance of clinical experience in promoting self-direct learning.Implications for Nursing Management: Nurse Managers are required to develop tailored strategies to support the transition process beyond the development of clinical competencies, with greater support for independence in learning—a crucial skill to become resilient and adaptable and to continually face the complexities of modern healthcare.

This research paper highlights and addresses the lack of a systematic review of the methods used to evaluate Learning Analytics (LA) and Learning Analytics Dashboards (LAD) of Adaptive Learning Platforms (ALPs) in the current literature. Addressing this gap, the authors built upon the work of Tretow-Fish and Khalid (2022) and analyzed 32 papers, which were grouped into six categories (C1-6) based on their themes. The categories include C1) the evaluation of LA and LAD design and framework, C2) the evaluation of user performance with LA and LAD, C3) the evaluation of adaptivity, C4) the evaluation of ALPs through perceived value, C5) the evaluation of Multimodal methods, and C6) the evaluation of the pedagogical implementation of ALP’s LA and LAD. The results include a tabular summary of the papers including the categories, evaluation unit(s), methods, variables and purpose. While there are numerous studies in categories C1-4 that focus on the design, development, and impact assessment of ALP's LA and LAD, there are only a few studies in categories C5 and C6. For the category of C5), very few studies applied any evaluation methods assessing the multimodal features of LA and LADs on ALPs. Especially for C6), evaluating the pedagogical implementation of ALP's LA and LAD, the three dimensions of signature pedagogy are used to assess the level of pedagogy evaluation. Findings showed that no studies focus on evaluating the deep or implicit structure of ALP's LA. All studies examine the structural surface dimension of learning activities and interactions between students, teachers, and ALP's LA and LAD, as examined in categories C2-C5. No studies were exclusively categorized as a C6 category, indicating that all studies evaluate ALP's LA and LAD on the surface structure dimension of signature pedagogy. This review highlights the lack of pedagogical methodology and theory in ALP's LA and LAD, which are recommended to be emphasized in future research and ALP development and implementation.

During the COVID-19 pandemic period, all the Sri Lankan universities delivered lectures in fully online mode using Virtual Learning Environments. In fully online mode, students cannot track their performance level, their progress in the course, and their performances compared to the rest of the class. This paper presents research work conducted at the University of Colombo School of Computing (UCSC), Sri Lanka, to solve the above problems and facilitate students learning in fully online and blended learning environments using Learning Analytics. The research objective is to design and create a Technology Enhanced Learning Analytics (TELA) dashboard for improving students’ motivation, engagement, and grades. The Design Science research strategy was followed to achieve the objectives of the research. Initially, a literature survey was conducted analyzing features and limitations in current Learning Analytic dashboards. Then, current Learning Analytic plugins for Moodle were studied to identify their drawbacks. Two surveys with 136 undergraduate students and interviews with 12 lecturers were conducted to determine required features of the TELA system. The system was designed as a Moodle Plugin. Finally, an evaluation of the system was done with third-year undergraduate students of the UCSC. The results showed that the TELA dashboard can improve students' motivation, engagement, and grades. As a result of the system, students could track their current progress and performance compared to the peers, which helps to improve their motivation to engage more in the course. Also, the increased engagement in the course enhances the student’s self-confidence since the student can see continuous improvement of his/her progress and performance which in turn improves the student’s grades.

This study aims to examine the effects of social support on EFL students’ self-directed learning (SDL) skills. Thus, a mixed-methods approach was adopted to design the study and answer the research questions: (1) What is the level of social support and self-directed learning skills among EFL students? (2) Is there a correlation between social support and self-directed learning skills among EFL students? (3) Does the gender of EFL students affect the level of their social support and self-directed learning skills? (4) In what ways does the relationship between social support and self-directed learning skills impact FLL? Data was collected via two sources (surveys and focus group interview) in which two hundred 367 students—199 male and 168 female—from the department of English language and literature at Mut'ah University participated in this study. First, the study findings revealed that family support scored the highest among other types of social support. Second, the assessment of the learning process was the most important among all SDL skills. Third, a significant positive correlation was found between social support and self-directed learning skills. Lastly, a significant difference in both levels of social support and self-directed learning skills among the EFL students, in favor of female students, was detected. Furthermore, the study offered implications for educators, EFL teachers, and policymakers.

Learning analytics (LA) dashboards are becoming increasingly available in various learning settings. However, teachers may face challenges in understanding and interpreting the data visualisations presented on those dashboards. In response to this, some LA researchers are incorporating visual cueing techniques, like data storytelling (DS), into LA dashboard design to reduce the data visualisation skills – often referred to as visualisation literacy (VL) – and cognitive effort required by teachers to effectively use dashboards. However, despite the potential of DS principles in simplifying data visualisations, there is limited evidence supporting their effectiveness in actually reducing teachers’ cognitive load. The study presented in this paper addresses this gap by investigating the potential impact of LA dashboards, with and without DS elements, on teachers with varying VL levels. Through a quasi-experimental study involving 23 teachers, we analysed changes in pupil dilation – a proxy for cognitive load – as they examined LA dashboards featuring student data captured while participating in synchronous, online collaborative learning tasks. Our findings suggest DS can reduce cognitive load, particularly for teachers with lower VL. These results provide insight into the effects of DS and VL on teachers’ cognitive load, thereby informing the design of LA dashboards. Implications for practice or policy:• Developers of LA dashboards need to pay more attention to incorporating visual and narrative elements that are easily comprehensible and target-oriented, based on users’ visualisation literacy levels.• Educational providers and LA designers can recommend dashboards with DS elements to teachers with low VL to enhance their work efficiency.

An existing Engineering Technology (ET) framework of Project-Based Learning (PBL) was examined for structure and rigor as a springboard to propose a robust PBL model, guided by three research questions: (a) What is the extent to which self-directed learning (SDL) skills were applied by final-year ET students in PBL, as determined quantitatively through the Self-Directed Learning Readiness Scale (SDLRS-A(r))?; (b) How are self-directed learning (SDL) skills, project management (PM) efficiencies, and change leadership (CL) effectiveness applied in the implementation of ET capstone projects?; and, (c) What are the best practices to accelerate PBL by employing SDL skills, PM efficiencies, and CL effectiveness? The mixed methodology research was conducted in two phases: Phase 1-Quantitative and qualitative: The SDLRS-A(r) Survey incorporating a 58-item questionnaire, six demographic items, and three open-ended questions on change leadership/change processes was administered to 30 Senior Design students graduating from an ET program; and, Phase 2-Qualitative: In-depth, one-on-one interviews with six student leaders from eight diverse, innovative capstone projects, and six faculty advisors who had facilitated these projects. Using SPSS 24.0, the SDLRS-A(r) questionnaire assessed the 30 Senior Design students' SDL skills in project implementation, using factor analysis to ascertain and compare a priori evidence. Additionally, textual analytic software (NVivo 11) graphically analyzed responses to the three open-ended questions for the Senior Design students' understanding of change leadership/change processes of their capstone projects through the Fall, Winter, and Spring terms of 2015-2016. Similarly, the semi-structured, one-on-one PBL interviews of six student team leaders and six faculty advisors were iteratively analyzed using graphical textual analytic software, Leximancer 4.5. The quantitative and qualitative analyses of the primary data identified essential elements of an accelerated PBL model through enhanced SDL skills, streamlined PM efficiencies, and, dynamic CL effectiveness. This PBL model is geared to yielding optimal outcomes with minimal loss of time and resources in rapidly evolving, technological environments in 21st century higher education. The study concluded that such an accelerated PBL model could also minimize the employment gap, fuel students' self-motivation, enable skill-building, and instill a deep commitment to life-long learning-in a competitive, technology-infused, and information-intensive world.

This study investigated role of the self-directed learning skills, metacognitive awareness, and 21st century skills and competences in predicting readiness for online learning during the COVID-19 pandemic. 21st Century Skills and Competences Scale, Self-Directed Learning Skills Scale, Metacognitive Awareness Inventory, and Readiness for Online Learning Scale were used to collect data from 834 prospective teachers. Structural equation modelling (SEM) results indicated that self-directed learning skills, metacognitive awareness, and 21st century skills and competences positively predict prospective teachers’ readiness for online learning. These findings suggested that enhancing prospective teachers’ self-directed learning, metacognitive awareness, and 21st century skills and competences may promote their readiness for online learning.

Background: Medical students need to acquire self-directed learning (SDL) skills for effective lifelong learning. Portfolios allow learners to reflect on their progress, diagnose learning needs and create learning plans, all elements of SDL. While mentorship is deemed to be essential for successful portfolio use, it is not known what constitutes effective mentorship in this process. In-depth understanding of the SDL construct seems a prerequisite.Aims: The aim of this study was to examine how portfolio mentors perceive and approach SDL.Methods: Interviews with faculty members who mentored medical students in portfolio were audio-recorded, transcribed and analysed for themes.Results: Eight mentors participated. Qualitative analysis revealed six major themes around mentors’ definitions of SDL, their perception of innate SDL abilities of medical students, their own approach to SDL, their understanding of the value of learning plans, their perceptions of students’ engagement with the portfolio and the impact of the portfolio process on the mentoring relationship.Conclusions: This study revealed tensions between mentors’ beliefs regarding the importance of SDL, their own approach to SDL and their perceptions of students’ SDL skills. Based on our analysis of these tensions, we recommend both explicit faculty development and institutional culture change for successful integration of SDL in medical education.

In this research, it was aimed to develop self-directed learning (SDL) skills of primary school students attending 1st-4th years and to design a self-directed learning model (PTSSDLM) for 4th grades. Action research model was used in this study. Self-directed learning skills were tried to be described through interviews done with students, teachers and parents and observations of students’ learning behaviors in classes. Depends on the results of the data obtained from interviews and observations, instructional intervention were done during seven weeks for developing students’ SDL planning skills. Data obtained during intervention weeks and at the end of the research were collected with audio records, field notes, researcher daily, students’ work sheets, reliability and validity committee’s meeting records, self-evaluation form, interviews done with students and class teacher. Findings obtained from data analysis revealed that students’ usage level of SDL planning skills were increased during the intervention. Based on findings obtained from the action research, A Teacher-Supported Self-Directed Learning Model was developed for primary school students attending 1st to 4th years.

Self-directed learning (SDL) skills serve as the basis for physician lifelong learning; however, residency training does not typically emphasize SDL skills. To understand residents' needs regarding SDL curricula, the authors used qualitative methods to examine the residency learning culture and residents' views of SDL. The authors conducted individual, in-depth, semistructured interviews with all 13 final-year residents at the Brown University Family Medicine Residency Program. Interviews were audio taped and transcribed verbatim. Using an iterative individual and group process, four researchers conducted a qualitative analysis of the transcripts, identifying major themes and higher-order interpretations. Major themes included resident beliefs about learning, the learning culture in residency, and developmental progress in learning. Four paradoxes emerged in the analysis: (1) Residents understand and value the concept of SDL, but they engage in limited goal setting and reflection and report lack of skills to manage their own learning, particularly in the clinical setting. (2) Despite being immersed in what aims to be a learner-centered culture, many residents still value traditional, teacher-centered approaches. (3) Residents recognize patient care as the most powerful stimulus for SDL, but they often perceive patient care and learning as competing priorities. (4) Residents desire external guidance for SDL. Graduating residents lacked confidence in their SDL skills and their ability to manage their learning, especially in clinical settings. Fostering SDL skills during residency will likely require training and guidance for SDL as well as changes in the structure and culture of residency.

The current shift from traditional classrooms to online learning in higher education calls for more attention to self-regulated learning. This research is motivated by the growing interest in potential of using learning analytics dashboard (LAD) to increase individuals' self-regulation by creating visibility into their performance in various applications. This study explores how data visualization can be integrated with online learning to improve learners' performance through enhancing their skills in planning and organization. We are working on the design of a comprehensive LAD, focusing on micro-level of learning analytics to support learning activities of students. The LAD includes the following two features to enhance students' self-regulation in online learning: (1) a function to track students' progress compared to other students' over time; (2) reminders to help students with upcoming deadlines and auto-generating to do lists. The hypothesis is that the LAD will increase students' engagement, motivation, and self-regulation in an online learning environment. This study is significant because it contributes to the body of knowledge by exploring how student-generated data can be used to improve self-regulated learning. The practical contribution of this study is to create a personalized LAD for students based on the learner-generated data to benefit students' organization skill, planning skill, and motivation.

Learning analytics dashboards commonly visualize data about students with the aim of helping students and educators understand and make informed decisions about the learning process. To assist with making sense of complex and multidimensional data, many learning analytics systems and dashboards have relied strongly on AI algorithms based on predictive analytics. While predictive models have been successful in many domains, there is an increasing realization of the inadequacies of using predictive models in decision-making tasks that affect individuals without human oversight. In this paper, we employ a suite of state-of-the-art algorithms, from the online analytics processing, data mining, and process mining domains, to present an alternative human-in-the-loop AI method to enable educators to identify, explore, and use appropriate interventions for subpopulations of students with the highest deviation in performance or learning process compared to the rest of the class. We demonstrate an application of our proposed approach in an existing learning analytics dashboard (LAD) and explore the recommended drill-downs in a course with 875 students. The demonstration provides an example of the recommendations from real course data and shows how recommendations can lead the user to interesting insights. Furthermore, we demonstrate how our approach can be employed to develop intelligent LADs.

Discovering the effects of learning analytics dashboard on students’ behavioral patterns using differential sequence mining

This paper describes a Human‐Centred Learning Analytics (HCLA) design approach for developing learning analytics (LA) dashboards for K‐12 classrooms that maintain both contextual relevance and scalability—two goals that are often in competition. Using mixed methods, we collected observational and interview data from teacher partners and assessment data from their students' engagement with the lesson materials. This DBR‐based, human‐centred design process resulted in a dashboard that supported teachers in addressing their students' learning needs. To develop the dashboard features that could support teachers, we found that a design refinement process that drew on the insights of teachers with varying teaching experience, philosophies and teaching contexts strengthened the resulting outcome. The versatile nature of the approach, in terms of student learning outcomes, makes it useful for HCLA design efforts across diverse K‐12 educational contexts. Practitioner notesWhat is already known about this topic Learning analytics that are aligned to both a learning theory and learning design support student learning. LA dashboards that support users to understand the associated learning analytics data provide actionable insight. Design‐based research is a promising methodology for Human‐Centred Learning Analytics design, particularly in the K‐12 educational context. What this paper adds Leveraging a longstanding, yet fluid, research‐practice partnership is an effective design‐based research adaptation for addressing the high variation in instructional practices that characterize K‐12 education. Using both quantitative and qualitative data that reflects students' developing knowledge effectively supports teachers' inquiry into student learning. Teachers' use of learning analytics dashboards is heavily influenced by their perspectives on teaching and learning. Implications for practice and/or policy Impact on student learning outcomes, alongside usability and feasibility, should be included as a necessary metric for the effectiveness of LA design. LA dashboard developers should both leverage learning data that reflect students' developing knowledge and position teachers to take responsive pedagogical action to support student learning. LA researchers and developers should utilize a long‐term, yet fluid, research‐practice partnership to form a multi‐stakeholder, multidisciplinary design team for Human‐Centred Learning Analytics design.

Introduction: In today's world, filled with technology and e-learning, readiness to participate in online educational environments is of great importance. Therefore, the present study was conducted with the aim of investigating the relationship between self-directed learning and information technology skills on the online learning readiness of nursing and midwifery students. Methods: This is an analytical cross-sectional study with a correlation design. The statistical population consisted of all nursing and midwifery students of the nursing and midwifery faculties of the Islamic Azad University of Mazandaran province, totaling 1,248 individuals in the academic year 2022-2023. A stratified random sampling method was employed, selecting 297 individuals (125 midwifery students and 172 nursing students) based on the Krejcie and Morgan table. Self-directed learning, information technology skills, and online learning were evaluated using questionnaires. The Kolmogorov-Smirnov test was used to assess the normality of the collected data. Data were analyzed in SPSS (version 16) using descriptive statistics, including mean, standard deviation by Pearson correlation coefficient statistics, and multiple linear regression at a significance level of 0.05. Results: According to multiple linear regression, the scores for online learning readiness were related to self-directed learning and information technology skills in nursing and midwifery students. The multiple correlation coefficient (R) was equal to 0.550. The coefficient of determination (R2) was equal to 0.492, which indicates that 49.2% of the changes in students' online learning readiness scores are explained by self-directed learning variables and their information technology skills. Conclusion: By recognizing and utilizing the distinct roles of self-directed learning and information technology skills, educators and policymakers can design support mechanisms based on the diverse needs of students. As a result, the online learning environment at Mazandaran Azad University can provide a more favorable and successful environment for students.