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This paper primarily aims to identify the multilevel learning processes emerging from abrupt telework implementation in a public knowledge-intensive organization (KIO) amid the COVID-19 crisis.

This single-case process research was guided by interpretivist epistemology. Empirical data from documentary research and 41 interviewed managers were processed by inductive qualitative analysis using the multilevel learning theoretical model.

Eight types and three modes of learning processes during the COVID-19 pandemic were identified in a public KIO, iteratively emerging in multilevel learning dynamics during the compulsory adoption of telework and replacing the face-to-face work mode conducted since its foundation.

As insider researchers, while daily and privileged access to the field was obtained, it also demanded their continuous effort to maintain transparency and scientific distancing; conceptual results are restricted to process theorisation studies, specifically the 4Is theoretical model in the scope of crisis learning process studies concerning KIOs.

This study provides evidence for managers to adopt interactive dynamics among eight multilevel types and three learning modes of emergent learning, developed during the COVID-19 pandemic, and support learning practices’ implementation and routinisation across three organizational levels in crisis situations. In addition, evidencing emergent types of learning enables organizational learning (OL) researchers to examine how organizational structures and work practices either promote or inhibit different learning types and impact multilevel learning when adopting teleworking during a crisis.

This research has theoretical value in two ways: (i) Providing empirically supported knowledge: This involves understanding multilevel learning processes resulting from emergent learning in a public KIO that abruptly adopted teleworking during a crisis context; (ii) deepening process theorization studies on OL: To achieve this, we enhance the 4I model by incorporating eight types and two modes of learning processes. These processes iteratively emerge from the individual and group levels towards the institutional level in a public KIO.

This systematic literature review aims to identify the pattern of data mining (DM) research by looking at the levels and aspects of education.

This paper reviews 113 conference and research papers from well-known publishers of educational data mining (EDM) and learning analytics-related research using a recognized literature review in computer science by Carrera-Rivera et al. (2022a). Two major stages, planning and conducting the review, were used. The databases of Elsevier, Springer, IEEE, SAI, Hindawi, MDPI, Wiley, Emerald and Sage were searched to retrieve EDM papers from the period 2017 to 2023. The papers retrieved were then filtered based on the application of DM to the three educational levels – basic, pre-tertiary and tertiary education.

EDM is concentrated on higher education. Basic education is not given the needed attention in EDM. This does not enhance inclusivity and equity. Learner performance is given much attention. Resource availability and teaching and learning are not given the needed attention.

This review is limited to only EDM. Literature from the year 2017 to 2023 is covered. Other aspects of DM and other relevant literature published in EDM outside the research period are not considered.

As the current trend of EDM shows an increase in zeal, future research in EDM should concentrate on the lower levels of education to identify the challenges of basic education which serves as the core of education. This will enable addressing the challenges of education at an early stage and facilitate getting a quality education at all levels of education. Appropriate EDM techniques for mining the data at this level should be the focus of the research. Specifically, techniques that can cater for the variation in learner abilities and the appropriate identification of learner needs should be considered.

Content sequencing is necessary in facilitating an easy understanding of concepts. Curriculum design from basic to higher education dwells much on this. Identifying the challenge of learning at the early stages will facilitate efficient learning. At the basic level of learning, data on learning should be collected by educational institutions just as it is done at the tertiary level. This will enable EDM to accurately identify the challenges and appropriate solutions to educational problems. Resource availability is a catalyst for effective teaching and learning. The attributes of a learner will enable knowing the true nature of the learner to determine the prospects of the learner.

This research has not been published in any journal. The information presented is the original knowledge of the authors. However, a pre-print of the work is in Research Square.

The purpose of this study is to present a systematic and comprehensive review of personalized, adaptive and semantic e-learning systems.

Preferred reporting items of systematic reviews and meta-analyses guidelines have been used for a thorough insight into associated aspects of e-learning that complement the e-learning pedagogies and processes. The aspects of e-learning systems have been reviewed comprehensively such as personalization and adaptivity, e-learning and semantics, learner profiling and learner categorization, which are handy in intelligent content recommendations for learners.

The adoption of semantic Web based technologies would complement the learner’s performance in terms of learning outcomes.

The evaluation of the proposed framework depends upon the yearly batch of learners and recording is a cumbersome/tedious process.

E-Learning systems may have diverse and positive impact on society including democratized learning and inclusivity regardless of socio-economic or geographic status.

A preliminary framework of an ontology-based e-learning system has been proposed at a modular level of granularity for implementation, along with evaluation metrics followed by a future roadmap.

This paper describes a model of “Learning to care” derived from a study exploring how care workers in care homes learn to care for people living with dementia. The “Learning to care” model is primarily informal in nature in which influences such as formalised training and organisational culture impact care outcomes indirectly rather than directly.

This study used a focused, critical ethnographic approach in two care homes in England resulting in 63 h of observation of care of people living with advanced dementia, 15 semi-structured interviews and 90 in-situ ethnographic interviews with care staff.

The findings reveal a three-level model of learning to care. At the level of day-to-day interactions is a mechanism for learning that is wholly informal and follows the maxim “What Works is What Matters”. Workers draw on resources and information within this process derived from their personal experiences, resident influences and care home cultural knowledge. Cultural knowledge is created through a worker’s interactions with colleagues and the training they receive, meaning that these organisational level influences affect care practice only indirectly via the “What Works is What Matters” mechanism.

This study makes an original contribution by explaining the nature of day-to-day informal learning processes as experienced by care workers and those living with dementia in care homes. In particular, it illuminates the specific mechanisms by which organisational culture has an effect on care practice and the limitations of formal training in influencing such practice.

Organisational learning (OL) is a critical capability family firms (FFs) need in order to adapt to an increasingly turbulent environment. Given the uniqueness of FFs and their differentiated decision-making processes, this review addresses fragmentation in the literature and synthesises prior research outlining the development of OL in FFs.

A systematic literature review was conducted using four databases, and 53 pertinent papers on OL in FFs published from 1998 to 2023 were analysed using the theory, characteristics, context and methodology (TCCM) framework.

The last five years (2019–2023) show a marked increase in interest in OL in FFs, with a rise in the number of quantitative studies. The findings indicate that OL is mainly studied as a unidimensional construct, while it is a multidimensional capability. Strategic management and organisational behaviour theories are commonly employed, while theories specific to family business such as socioemotional wealth (SEW) and familiness are underrepresented. Most studies focus on FFs in the Northern Hemisphere, and few studies examine OL in FFs located in the Global South. The TCCM framework reveals the complexity and multi-layered nature of OL in FFs.

This is one of the first systematic reviews to synthesise research on OL in FFs. The proposed research agenda identifies fruitful areas for future investigations concentrating on the multidimensional nature of OL, family-related outcomes, as well as contextual and methodological research directions of interest to family business researchers.

The purpose of this study was to examine entrepreneurs’ learning before, during and after entrepreneurial failure and understand the relationship between learning and recovery from failure.

A qualitative multiple case study was carried out based on entrepreneur interviews who have experienced the failure of their businesses.

The study finds that entrepreneurs learn both during the company’s lifespan and post-failure, with distinct types and intensities of learning at different life cycle phases. It highlights the link between learning and emotions during the failure process, revealing entrepreneurs’ limited awareness of their knowledge gaps, particularly during successful business phases, and shows the difference between women and men.

One limitation of this study is that the companies are all located in northern and central Portugal, and the number of entrepreneurs starting new ventures post-failure is limited. Another is a lack of comprehensive measurement of the economic impact, especially on the health of individuals who have experienced the impact of failure. The absence of concrete data hampers understanding and the development of targeted support mechanisms for these individuals.

This study stands out for its unique approach, thoroughly exploring the intricate, profound and significant experiences during a crisis, such as a business failure, from the entrepreneurs’ perspective. It delves into their learning processes before, during and after the failure, providing a comprehensive understanding. This study evidence that significant learning occurs during the operation of the business, and not during or after failure, due to the limitations imposed by the pain and disorientation it causes. Therefore, if recovery does not occur, learning does not happen either. It also highlights the differences between women and men in their learning experiences, adding a new dimension to the research.

Student engagement evaluation is considered to be connected to many aspects of the management of higher education, but outside Western higher education, research and evaluation on student engagement and experiences has been limited so far. Our study focuses on the underexplored aspects of Palestinian higher education with the aim of gaining an actionable understanding from the overall student engagement situation to enhance the management and development of local teaching and learning practices.

A quantitatively oriented, sequential mixed-methods design was adopted. With the applied and validated engagement measurement we collected 946 engagement questionnaire responses from Palestinian university students. Quantitative data were analysed using structural equation modelling, K-means cluster analysis and chi-squared tests. Inductive and deductive thematic analysis was employed for the open answers.

With the three validated student engagement dimensions, the applied cluster analysis allowed three different engagement profile groups to be distinguished: strongly, moderately and loosely engaged. In the subsequent statistical and qualitative thematic analyses, these three engagement clusters differ in the degree to which they had a clear vision of a future profession or in their academic engagement with their studies. Moreover, qualitative analysis brought up many shared concerns regarding theoretically oriented studies and uncertain professional and career prospects in the Palestinian higher education context.

This study is one of the first attempts to develop tools for student engagement management in Palestinian higher education. The study findings are particularly significant for developing micro- and meso-level management practices in Palestinian higher education institutions.

This study aims to present the evaluation of a competency-based online professional development training program, PhD Progression, tied to a digital badge system, created to support PhD students across fields.

This study took place at Boston University, a large, nonprofit, Carnegie Classified R1 research-intensive institution located in the northeastern region of the USA. Through internal campus collaborations, the authors developed a PhD core capacities framework. Building from this framework, the authors designed the first learning level of the program and ran a pilot study with PhD students from various fields and at different stages of their PhD. Using surveys and focus groups, the authors collected both quantitative and qualitative data to evaluate this program.

The quantitative and qualitative data show that the majority of the PhD student participants found the contents of the competency-based training program useful, appropriate for building skills and knowledge and therefore relevant for both their degree progress and their future job. Gaining digital badges significantly increased their motivation to complete training modules.

This type of resource is scalable to other institutions that wish to provide self-paced professional development support to their PhD students while rewarding them for investing time in building professional skills and enabling them to showcase these skills to potential employers.

This study demonstrates, for the first time, that tying a digital badging system to a competency-based professional development program significantly motivates PhD students to set professional development goals and invest time in building skills.

Professional learning networks (PLNs) involve teachers’ collaboration with others outside of their school to improve teaching and learning. PLNs can facilitate teachers’ professional growth and school improvement. This study aims to explore the drivers for participation within PLNs, the enactment process and the impact of PLN participation on teachers, students and schools in Greece.

A descriptive phenomenological study was conducted to explore the lived experience of primary school teachers participating in PLNs.

The findings showed that individuals who were open to change were driving innovation to address a need or a lack in their daily practice that was not satisfied within their usual community of practice. The key element of the participation was peer collaboration with openness of communication without attendant accountability pressures. The change was mainly identified in teacher skills and the school climate. An individual could bring change only if the school is already open to change. In some cases, resistance to change in schools was identified before enactment or during enactment. The transformation of teachers’ and leaders’ stances is discussed, enabling the opportunity to maximise school improvement.

The study examines PLNs as European Union-funded initiatives that are developed by teachers in centralised education systems under the phenomenological research paradigm. It explores the PLNs in a different setting compared to the existing conceptual theory of change for PLNs.

Assembly action recognition plays an important role in assembly process monitoring and human-robot collaborative assembly. Previous works overlook the interaction relationship between hands and operated objects and lack the modeling of subtle hand motions, which leads to a decline in accuracy for fine-grained action recognition. This paper aims to model the hand-object interactions and hand movements to realize high-accuracy assembly action recognition.

In this paper, a novel multi-stream hand-object interaction network (MHOINet) is proposed for assembly action recognition. To learn the hand-object interaction relationship in assembly sequence, an interaction modeling network (IMN) comprising both geometric and visual modeling is exploited in the interaction stream. The former captures the spatial location relation of hand and interacted parts/tools according to their detected bounding boxes, and the latter focuses on mining the visual context of hand and object at pixel level through a position attention model. To model the hand movements, a temporal enhancement module (TEM) with multiple convolution kernels is developed in the hand stream, which captures the temporal dependences of hand sequences in short and long ranges. Finally, assembly action prediction is accomplished by merging the outputs of different streams through a weighted score-level fusion. A robotic arm component assembly dataset is created to evaluate the effectiveness of the proposed method.

The method can achieve the recognition accuracy of 97.31% and 95.32% for coarse and fine assembly actions, which outperforms other comparative methods. Experiments on human-robot collaboration prove that our method can be applied to industrial production.

The author proposes a novel framework for assembly action recognition, which simultaneously leverages the features of hands, objects and hand-object interactions. The TEM enhances the representation of dynamics of hands and facilitates the recognition of assembly actions with various time spans. The IMN learns the semantic information from hand-object interactions, which is significant for distinguishing fine assembly actions.