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Cybersecurity competitions can effectively develop skills, but engaging a wide learner spectrum is challenging. This study aims to investigate the perceptions of cybersecurity competitions among Reddit users. These users constitute a substantial demographic of young individuals, often participating in communities oriented towards college students or cybersecurity enthusiasts. The authors specifically focus on novice learners who showed an interest in cybersecurity but have not participated in competitions. By understanding their views and concerns, the authors aim to devise strategies to encourage their continuous involvement in cybersecurity learning. The Reddit platform provides unique access to this significant demographic, contributing to enhancing and diversifying the cybersecurity workforce.

The authors propose to mine Reddit posts for information about learners’ attitudes, interests and experiences with cybersecurity competitions. To mine Reddit posts, the authors developed a text mining approach that integrates computational text mining and qualitative content analysis techniques, and the authors discussed the advantages of the integrated approach.

The authors' text mining approach was successful in extracting the major themes from the collected posts. The authors found that motivated learners would want to form a strategic way to facilitate their learning. In addition, hope and fear collide, which exposes the learners’ interests and challenges.

The authors discussed the findings to provide education and training experts with a thorough understanding of novice learners, allowing them to engage them in the cybersecurity industry.

We argue this method of inquiry better represents the participants' learning, lives and experiences in the formal neoliberal education system prioritising performativity, categorising and ranking students.

The paper explores using poetry as a research method to reveal the learning experiences of adult learners, who have often had disruptive experiences of the formal schooling system and return to study in community-based education spaces. Inspired by Laurel Richardson’s transgressive technique of presenting sociological data through poetry as method, we use poetic representations of these learners' lives alongside case study research methodology. The research was conducted in conjunction with Neighbourhood Houses in Victoria, Australia. Qualitative data were generated through conducting multiple case studies of learners across various adult community education (ACE) sites. In this research, some case studies were presented in the traditional method of writing biography, others were written in the form of found poetry, which we refer to as data as poetry and text. The paper uses found poetry through participant-voiced poems written from interview transcripts. We argue this method of inquiry better represents the participants' learning, lives and experiences in the formal neoliberal education system prioritising performativity, categorising and ranking students. Our findings highlight the benefits of using poetry to communicate data in case study research as it effectively represents the experiences of adult learners' lives in a creative and concise form, transgressing normative practices of writing education research. These poetic representations of data reveal learner experiences in an embodied and agentic way while providing readers with a deep and rich understanding of these crucial adult learning spaces.

Our findings highlight the benefits of using poetry to communicate data in case study research as it effectively represents the experiences of adult learners' lives in a creative and concise form, transgressing normative practices of writing education research.

This research paper is empirical research and has not been submitted elsewhere for publication.

Our study aims to focus on the application of knowledge mapping to provide pedagogically-structured learners' competences.

We conducted an experiment examined the associations between the pedagogical quality of students’ pedagogically-informed knowledge (PIK) maps, class assignment scores and perceptions of PIK mapping’s uses.

The results showed that higher assignment scores were significantly predicted by higher quality PIK maps, ratings for PIK mapping were significantly higher than other mappings, and the learners’ experience of PIK mapping led to a significant change of attitude towards mapping as a learning activity and to a positive opinion of the value of PIK mapping in particular. Interestingly, there was no significant relation between learners’ opinion ratings of the uses of PIK mapping in learning and their assignment scores.

Questions remain on the generalizability of the findings, and on the features of a PIK map which are particularly useful to a learner. This study investigated the value of PIK mapping in the context of a practical class on the building of simple DIY (do-it-yourself) holographic projectors; it may be thought that the applied nature of the topic was more suited to the PIK mapping of learner competences and intended learning outcomes than a more theoretic classroom topic on holography. A future study is planned to address this issue.

While the Chinese securities market is booming, the phenomenon of listed companies falling into financial distress is also emerging, which affects the operation and development of enterprises and also jeopardizes the interests of investors. Therefore, it is important to understand how to accurately and reasonably predict the financial distress of enterprises.

In the present study, ensemble feature selection (EFS) and improved stacking were used for financial distress prediction (FDP). Mutual information, analysis of variance (ANOVA), random forest (RF), genetic algorithms, and recursive feature elimination (RFE) were chosen for EFS to select features. Since there may be missing information when feeding the results of the base learner directly into the meta-learner, the features with high importance were fed into the meta-learner together. A screening layer was added to select the meta-learner with better performance. Finally, Optima hyperparameters were used for parameter tuning by the learners.

An empirical study was conducted with a sample of A-share listed companies in China. The F1-score of the model constructed using the features screened by EFS reached 84.55%, representing an improvement of 4.37% compared to the original features. To verify the effectiveness of improved stacking, benchmark model comparison experiments were conducted. Compared to the original stacking model, the accuracy of the improved stacking model was improved by 0.44%, and the F1-score was improved by 0.51%. In addition, the improved stacking model had the highest area under the curve (AUC) value (0.905) among all the compared models.

Compared to previous models, the proposed FDP model has better performance, thus bridging the research gap of feature selection. The present study provides new ideas for stacking improvement research and a reference for subsequent research in this field.

The proliferation of lean principles in the construction industry is offset by the enduring uncertainty among industry stakeholders regarding their respective roles in lean implementation. This uncertainty is further compounded by the scarcity of empirical investigations in this area. Consequently, this study undertakes the task of bridging this knowledge gap by identifying the critical roles of lean learners and their indispensable contributions to achieving successful lean implementation.

A qualitative exploratory approach informed by an interpretivism perspective was adopted. The case study strategy was employed to gather data from three contracting organisations that had implemented lean practices. Empirical data was collected through in-depth semi-structured interviews with fifteen industry experts and complemented by document reviews. To analyse the data, a code-based content analysis approach was employed using NVivo software, while Power BI software was utilised to develop a comprehensive force-directed graph visualisation.

The research findings substantiated nine lean learners and unveiled a set of seventy-three roles associated with them. The force-directed graph facilitated the identification of lean learners and their connections to the emerged roles. Notably, the graph highlighted the pivotal role played by project managers and internal lean trainers in ensuring the success of lean implementation, surpassing the contributions of other lean learners.

The implications of findings extend to industry professionals seeking to establish a robust lean learning framework to expedite lean implementation within the construction sector. This study not only provides a comprehensive definition of lean learners’ roles but also transcends specific construction types, making it a significant catalyst for global impact.

The purpose of this study is to develop an intelligent tutoring system (ITS) for programming learning based on information tutoring feedback (ITF) to provide real-time guidance and feedback to self-directed learners during programming problem-solving and to improve learners’ computational thinking.

By analyzing the mechanism of action of ITF on the development of computational thinking, an ITF strategy and corresponding ITS acting on the whole process of programming problem-solving were developed to realize the evaluation of programming problem-solving ideas based on program logic. On the one hand, a lexical and syntactic analysis of the programming problem solutions input by the learners is performed and presented with a tree-like structure. On the other hand, by comparing multiple algorithms, it is implemented to compare the programming problem solutions entered by the learners with the answers and analyze the gaps to give them back to the learners to promote the improvement of their computational thinking.

This study clarifies the mechanism of the role of ITF-based ITS in the computational thinking development process. Results indicated that the ITS designed in this study is effective in promoting students’ computational thinking, especially for low-level learners. It also helped to improve students’ learning motivation, and reducing cognitive load, while there’s no significant difference among learners of different levels.

This study developed an ITS based on ITF to address the problem of learners’ difficulty in obtaining real-time guidance in the current programming problem-solving-based computational thinking development, providing a good aid for college students’ independent programming learning.

This study probed the impact of using learning technologies (LT) on developing Yemeni English as a foreign language (EFL) students' autonomy and creativity toward English language learning. Also, the research gauged if LT impacts learners' autonomy and creativity across gender and university-type variables.

The study utilized a valid and reliable questionnaire, comprising 20 close-ended items, which was administered to 109 Yemeni EFL undergraduate students.

The researchers found that LT positively impacts learners' creativity and autonomy, with mean scores of 4.09 and 3.86, respectively. Furthermore, the results showed a medium correlation between creativity and autonomy with a correlation coefficient of r = 0.63 at a probability of Sig = 0.00. Likewise, the results revealed that LT impacted female learners' creativity more significantly than their male counterparts (Sig = 0.047). Nevertheless, no significant differences were found pertaining to the impact of LT on students' autonomy across public and private universities (Sig = 0.213).

EFL teachers are advised to encourage their students' autonomy and creativity throughout their lifelong learning journey in order to adapt to the ever-changing demands of the world.

This study investigates the impact of learning technology on Yemeni EFL students' autonomy and creativity.

Digitalisation is reshaping the learning process, shifting it towards personalisation and online learning, and fuelling the growth of massive open online courses (MOOCs) and micro-credentials. Despite being a popular global trend, limited studies have looked at micro-credentials and their impact on learners' behavioural outcomes. The purpose of this study is to investigate the impact of programme design factors on learning experience, as well as the inter-relationships between programme design, learning experience and behavioural responses (e.g. engagement and willingness to pay more (WTPM)) towards micro-credentials. In addition, the study aims to investigate learning enjoyment as a moderator.

A survey questionnaire was used to collect data from 354 respondents who are working adults living in the major economic states in Malaysia. Data analysis was performed using the analysis of a moment structures (AMOS) statistical software and SPSS (Statistical Package for the Social Sciences) PROCESS macro.

The results show the significance of programme design factors (i.e., flexibility, system quality and content quality) in determining the learning experience. The learning experience is found as a mediator in the relationship between programme design factors and learner engagement and WTPM. In addition, the moderation assessment confirms that enjoyment during learning strengthens the relationship between experience and behavioural responses.

This study is amongst a few selected studies that focus on engagement in and WTPM for micro-credentials. In addition, it emphasises the mediating role of the learning experience and the moderating role of enjoyment in understanding the impact of programme design on learners' experiences and behavioural responses.

This study intends to investigate the determinants of learners' continuance intention to use massive open online courses (MOOCs) for personal or professional development.

This study employed quantitative research design. The respondents were individual learners from six selected universities in China who used MOOCs for continuous learning. A purposive sampling technique was employed to obtain 270 valid samples. Data were analyzed and analytical outputs were produced using the techniques of Partial Least Squares Structural Equation Modeling and Importance-Performance Matrix.

Expectation confirmation was found to have a positive relationship with perceived usefulness, flow experience, learning self-efficacy and satisfaction with MOOCs. Perceived usefulness, flow experience and leaning self-efficacy were also found to have a positive relationship with MOOC satisfaction. In addition, perceived usefulness, flow experience, learning self-efficacy and MOOC satisfaction had a positive impact on continuance usage intention.

The outcomes of the study can serve as a practical reference for MOOC providers and decision-makers to develop relevant strategies to increase the course completion rates.

This study aims to investigate a unique approach to learning languages through self-directed online learning. Specifically, it explores the self-management abilities and skills learners need while learning a language outside traditional classroom settings when using mobile-assisted learning technology.

A mixed-methods approach was used in this study, including an online survey of 84 people and 10 semi-structured interviews.

Findings reveal the significant role of specific and well-defined learning goals in enhancing learners’ performance. These goals can be either self-initiated by the learners themselves or defined by the technological features of the learning platform. However, the presence of distractions in learners’ daily lives presents challenges to effective time management, affecting learners both physically and psychologically. A key aspect of self-directed language learning lies in the learners’ ability to seek out relevant human and material resources beyond the confines of a single mobile-assisted language learning (MALL) tool. The authenticity of these resources is crucial in ensuring meaningful and effective learning experiences.

Understanding how learners navigate and discover valuable resources is a central focus of this study. This research offers valuable insights into the field of self-directed language learning, revealing the pivotal role of self-management skills with mobile-assisted learning technology. The findings contribute to the broader field of language education and offer practical implications for educators and developers seeking to optimize self-directed language learning experiences through innovative and technologically driven approaches.

MALL is often ideal for individualized informal learning, but the existing literature focuses heavily on formal learning situations, underestimating the importance of MALL practices in various informal settings. Most research reports on MALL-based self-directed learning primarily sample traditional English-learning university students. Therefore, there is a need for research on how nontraditional older adult learners self-direct their language learning with mobile technology outside the classroom.