Search results

This paper presents the phenomenographic analysis of students' approaches to learning in the first year architectural design coursework; thereby correlating contextualization in the architectural curriculum.

This paper reviews phenomenographic data of first year architecture students' learning experience through a comparative analysis of first- and fourth-year students' approaches to learning in the design studio; further co-relating this analysis to the final classification involving all five years of students' learning approaches in the architecture program.

Five meta-categories of the comparative analysis and nineteen meta-categories of the final classification are evaluated using first-year students' learning approaches – to understand the importance of contextualization in curriculums of architecture.

This phenomenographic analysis of first-year students' learning experience represents the onward journey from surface-to-deep approaches to learning that is encountered in their learning approaches, pertaining to the design process in the design coursework during five years of architectural education.

This paper systematically extends the discussion of first year architecture students' engagement in the design process that leads to deep learning; further delving into the static dimension of knowledge and its extension to the dynamic dimension of knowing architecture.

A mixed-method study was performed to determine the impact of integrating systems thinking (ST) into an electronic learning module for junior high school teachers in the Philippines. The study aims to assess how an ST approach to pedagogy compared against a conventional approach in terms of contribution to the participants’ global climate change content knowledge, holistic thinking and depth and accuracy of knowledge and reasoning.

The study implemented e-learning modules using an ST approach versus a conventional approach in teaching climate science to junior high school teachers. The paper presents quantitative data obtained from pre and posttests results of the 20 teacher-participants and qualitative data obtained during the focus-group discussion (FGD) after the implementation of the study.

The results from the statistical analysis indicated that the ST group obtained a significant increase in their assessment scores compared to the non-ST group, according to predetermined criteria. Content knowledge, depth and accuracy of knowledge and reasoning increased the most. The participants mentioned during the FGD that the module helped deepen their understanding of climate change.

The study was limited to 20 teacher-participants, but it has relevance for public school teachers in the country given that participants had raised concerns regarding the lack of training in their schools for teaching climate science. They admitted that they lacked critical information to include in climate change topics in their classes.

This paper shows how the ST approach can be used to teach climate change to junior high students. The e-learning module can provide teachers with better understanding, knowledge and reasoning to teach climate change to high school students more effectively.

This study aims at understanding how higher education institutions (HEIs) can contribute to sustainable development, by designing their programmes for bringing about a transformative impact on communities and students, and also to examine what alternative pedagogical approaches could be used for that. In the past decades, HEIs have increasingly created social innovation (SI) programmes, as a way to achieve United Nations Sustainable Development Goals. These community-oriented and field-based programmes are difficult to ally with conventional classroom education. This study explores how these programmes could integrate the participatory approach and what would be the benefits. It also investigates the effectiveness of the experiential learning approach for teaching sustainability.

A case study method is used to document SI projects initiated by an HEI programme in rural India.

It was found that the participatory approach contributes to empowering communities and also benefits the students in terms of academic, professional and personal growth. Empirical findings show that experiential learning is an efficient method to teach sustainability. Ultimately, both pedagogical approaches are found to be mutually beneficial.

This study fills a gap in the literature, by providing empirical evidence on how HEI can implement innovative educational strategies such as participatory approach and experiential learning in their programmes towards teaching sustainability. A conceptual model for HEI interested in developing similar programmes is also proposed. To the best of the authors’ knowledge, this study is one of the first studies focusing on the context of Indian HEI.

With the increasing number of Web services, correct and efficient classification of Web services is crucial to improve the efficiency of service discovery. However, existing Web service classification approaches ignore the class overlap in Web services, resulting in poor accuracy of classification in practice. This paper aims to provide an approach to address this issue.

This paper proposes a label confusion and priori correction-based Web service classification approach. First, functional semantic representations of Web services descriptions are obtained based on BERT. Then, the ability of the model is enhanced to recognize and classify overlapping instances by using label confusion learning techniques; Finally, the predictive results are corrected based on the label prior distribution to further improve service classification effectiveness.

Experiments based on the ProgrammableWeb data set show that the proposed model demonstrates 4.3%, 3.2% and 1% improvement in Macro-F1 value compared to the ServeNet-BERT, BERT-DPCNN and CARL-NET, respectively.

This paper proposes a Web service classification approach for the overlapping categories of Web services and improve the accuracy of Web services classification.

The purpose of this study is to explore how digital technologies at work serve as environments for informal workplace learning in knowledge work.

Digital ethnography was used to investigate the digital environments of one public sector workplace. The data included observations, interviews and participant diaries.

The digital work environment consisted of a complex network of technologies and people connected to them. The ethnographic accounts revealed both expansive and restrictive features of the digital environment. Digital technology extended learning opportunities by providing flexible possibilities for interaction, collaboration and access to a wealth of information. On the contrary, digitally mediated presence could restrict learning if the attendance and learning remained superficial. The complexity and constant change in digital workplace environments presented challenges that could potentially restrict learning. Information overload, constant interruptions and changes were burdens that required employees’ skills to manage these challenges.

The authors take a novel approach to view the workplace as a phygital environment in which social, physical and digital environments are combined. Because digital environments are becoming increasingly essential parts of the workplace, it is important to understand how they can support learning.

Organisations are investing in systems such as product lifecycle management (PLM) to support product development, collaboration across complex supply chains and to provide a framework for digital transformation. Graduates of apparel programmes would benefit from a knowledge of PLM to help realise the opportunities that PLM offers. The purpose of this paper is to report on an educational research project that used PLM as a context for practice-based learning and as a mechanism to update the learning experience and stimulate the development of future practice.

This paper reports on the experiences, critical reflections and data from an action research study to establish a learning community through an educational partnership for PLM software within an undergraduate fashion business course. The cohort of the first year of the intervention (n = 28) is the main study population.

The findings indicate that PLM provided a stimulating learning context supportive of a detailed understanding of current industry practice, critical and innovative thinking and the development of a professional identity.

The opportunity for the development of both industry and educational practice is outlined.

A general introduction to PLM provides important information to support and advance Fashion Industry 4.0. Educational partnerships can reduce barriers to the integration of advanced technologies into the higher education curriculum.

Applications of PLM are under researched in textiles and apparel. The paper contributes to the broadening of the knowledge base of PLM and its potential to achieve strategic transformation of the sector.

The research aims at examining educators’ perceptions, attitudes and behavioral intentions toward learning analytics (LA) and the role of self-instruction within the proposed model for LA adoption.

A quantitative approach is utilized in which a questionnaire is designed as a tool for data collection and partial least squares structural equation modeling (PLS-SEM) is used for data analysis and model testing.

Results show that performance expectancy and effort expectancy have a significant effect on educators’ attitudes, which in turn significantly affect educators’ behavioral intentions. Self-instruction mediates the relationship between educators’ attitudes and behavioral intentions. The attitude towards LA mediates the relationship between LA performance expectancy and educators’ self-instruction. The research model explains 54% of the variance in learning analysis adoption.

Findings open a path for research on pedagogical factors affecting LA adoption and guide education managers toward facilitating LA adoption. The tested model contributes to LA and teaching and learning literature by highlighting the role of educators’ self-instruction in LA adoption.

This study aims to understand how to develop, support and utilize professional learning community (PLCs) to build organizational capacity to support teacher learning and collaboration. Although literature highlights the importance of leadership in creating a PLC, there is little research on specific actions leaders can take to create an authentic, sustainable PLC.

We employed a multicase study approach at three school sites within the same district. Our research was guided by the following questions: (1) How are learning communities developed and sustained in school settings?; (2) What is the role of administrators in cultivating learning communities?; and (3) What factors contribute to and hinder the success of learning communities?

Despite being in the same school district, the three schools’ PLCs operated differently. The schools displayed characteristics of PLCs, with minimal implementation of all components. Developing a professional learning community at all three sites began with implementing structural factors and mandating specific activities such as weekly grade-level planning. Social factors were much more complex to control by administration, affecting the fidelity of learning and collaboration within the PLCs.

Although the literature highlights the importance of leadership in creating a PLC, there is little research that supports specific actions leaders can take to create an authentic, sustainable community of practice. In addition, there is limited literature supporting how administrators use PLCs to build organizational capacity and support teacher learning. Our study contributes to building the empirical knowledge base related to these two areas.

The aim is to understand how goal orientation may help entrepreneurs maintain life satisfaction when faced with multiple crisis episodes. To do so, the authors study the early impact of COVID-19 on the life satisfaction of entrepreneurs who were previously faced with venture distress.

Data on 164 Belgian entrepreneurs, who were faced with previous venture distress, are used. The analysis is quantitative, and uses survey data, in combination with databases. The survey was administered in the beginning of the COVID-19 pandemic (June 2020).

Entrepreneurs high in learning goal orientation are less likely, and those high in performance-avoidance orientation are more likely to experience a decline in life satisfaction. Additionally, the time span between the two crises moderates the relationship between learning goal orientation and life satisfaction. Particularly, entrepreneurs high in learning goal orientation are less likely to experience a decline in life satisfaction if more time has passed between venture distress and the COVID-19 crisis.

Often, entrepreneurs are faced with multiple episodes of distress. The authors study entrepreneurs who have been in venture distress before and are then confronted with the COVID-19 crisis. The study shows that goal orientation, which is a type of self-regulation, plays an important role in how entrepreneurs’ life satisfaction is affected. Also, the authors find that the time between distress events matters. These are important insights for practitioners, including entrepreneurs and support providers.

The study adds to the emerging discussion on the impact of crises on entrepreneurs. It studies life satisfaction (a measure of well-being) and complements studies that examine the impact of crises, on entrepreneurs’ actions and firm performance.

Taking into consideration the current human need for agricultural produce such as rice that requires water for growth, the optimal consumption of this valuable liquid is important. Unfortunately, the traditional use of water by humans for agricultural purposes contradicts the concept of optimal consumption. Therefore, designing and implementing a mechanized irrigation system is of the highest importance. This system includes hardware equipment such as liquid altimeter sensors, valves and pumps which have a failure phenomenon as an integral part, causing faults in the system. Naturally, these faults occur at probable time intervals, and the probability function with exponential distribution is used to simulate this interval. Thus, before the implementation of such high-cost systems, its evaluation is essential during the design phase.

The proposed approach included two main steps: offline and online. The offline phase included the simulation of the studied system (i.e. the irrigation system of paddy fields) and the acquisition of a data set for training machine learning algorithms such as decision trees to detect, locate (classification) and evaluate faults. In the online phase, C5.0 decision trees trained in the offline phase were used on a stream of data generated by the system.

The proposed approach is a comprehensive online component-oriented method, which is a combination of supervised machine learning methods to investigate system faults. Each of these methods is considered a component determined by the dimensions and complexity of the case study (to discover, classify and evaluate fault tolerance). These components are placed together in the form of a process framework so that the appropriate method for each component is obtained based on comparison with other machine learning methods. As a result, depending on the conditions under study, the most efficient method is selected in the components. Before the system implementation phase, its reliability is checked by evaluating the predicted faults (in the system design phase). Therefore, this approach avoids the construction of a high-risk system. Compared to existing methods, the proposed approach is more comprehensive and has greater flexibility.

By expanding the dimensions of the problem, the model verification space grows exponentially using automata.

Unlike the existing methods that only examine one or two aspects of fault analysis such as fault detection, classification and fault-tolerance evaluation, this paper proposes a comprehensive process-oriented approach that investigates all three aspects of fault analysis concurrently.