This study examines diverse information media in order to identify those formats that are most suitable for consumption via handheld mobile devices, namely, smartphones and tablets. The preferences of the users are measured objectively by analyzing actual data of their relative use of handheld mobile devices and personal computing (PC) desktop devices, including laptops and notebooks, for consumption of information presented in various formats. Our findings are based on Google Analytics pageview data of five course Websites during a period of three semesters, by 11,557 undergraduate students. M-learning contexts were chosen, since in a learning environment the interests of information providers (i.e., the instructors) are in accord with those of the information consumers (i.e., the students), whereas in commercial settings there may be conflicts of interests. Our findings demonstrate that although about 90% of the pageviews were via PC devices, the rate of smartphone use for consuming learning content in diverse information media is gradually increasing as time goes by, whereas the rate of tablet use for these purposes is stagnant. The most promising direction for smartphone development, emanating from the findings, is online video content.

Aim/Purpose: The primary objective of this research is to build an enhanced framework for Applied and Computational Math. This framework allows a variety of applied math concepts to be organized into a meaningful whole. Background: The framework can help students grasp new mathematical applications by comparing them to a common reference model. Methodology: In this research, we measure the most frequent words used in a sample of Math and Computer Science books. We combine these words with those obtained in an earlier study, from which we constructed our original Computational Math scale. Contribution: The enhanced framework improves the Computational Math scale by integrating selected concepts from the field of Data Science. Findings: The resulting enhanced framework better explains how abstract mathematical models and algorithms are tied to real world applications and computer implementations. Future Research: We want to empirically test our enhanced Applied and Computational Math framework in a classroom setting. Our goal is to measure how effective the use of this framework is in improving students’ understanding of newly introduced Math concepts.

Aim/Purpose: The purpose of this article is to establish the different impacts of technological changes in institutions generating irrevocable changes in today’s society. Background: Technological changes have had a positive impact on many aspects of everyday life today, and it is natural that both public and private institutions benefit from this reality. Methodology: The research method used is based on the explanatory approach, through the documentary review of secondary sources and research works. Contribution: The implementation of electronic government in Ecuador is presented as a direct consequence of these technological developments with ways to direct and govern a country, which leads to competitive advantages in a world that is increasingly globalized. Findings: In the institutions the only permanent thing is change, for which the changing and evolving fact that the public and private institutions of today must have is highlighted. Recommendations for Practitioners: Results can inform to users the importance of the “new government” in a practical level. Recommendation for Researchers: The influence of technology on how to govern and if this in some way improves the functioning of the State. Impact on Society: Technological developments, which leads competitive advantages in a world that is increasingly globalized. Future Research: Create discussion and have a starting point to compare the influence of technological government in different parts of the world.

Aim/Purpose: Although cassava is one of the crops that can be grown during the dry season in Northeastern Thailand, most farmers in the region do not know whether the crop can grow in their specific areas because the available agriculture planning guideline provides only a generic list of dry-season crops that can be grown in the whole region. The purpose of this research is to develop a predictive model that can be used to predict suitable areas for growing cassava in Northeastern Thailand during the dry season. Background: This paper develops a decision support system that can be used by farmers to assist them determine if cassava can be successfully grown in their specific areas. Methodology: This study uses satellite imagery and data on land characteristics to develop a machine learning model for predicting suitable areas for growing cassava in Thailand’s Nakhon-Phanom province. Contribution: This research contributes to the body of knowledge by developing a novel model for predicting suitable areas for growing cassava. Findings: This study identified elevation and Ferric Acrisols (Af) soil as the two most important features for predicting the best-suited areas for growing cassava in Nakhon-Phanom province, Thailand. The two-class boosted decision tree algorithm performs best when compared with other algorithms. The model achieved an accuracy of .886, and .746 F1-score. Recommendations for Practitioners: Farmers and agricultural extension agents will use the decision support system developed in this study to identify specific areas that are suitable for growing cassava in Nakhon-Phanom province, Thailand Recommendation for Researchers: To improve the predictive accuracy of the model developed in this study, more land and crop characteristics data should be incorporated during model development. The ground truth data for areas growing cassava should also be collected for a longer period to provide a more accurate sample of the areas that are suitable for cassava growing. Impact on Society: The use of machine learning for the development of new farming systems will enable farmers to produce more food throughout the year to feed the world’s growing population. Future Research: Further studies should be carried out to map other suitable areas for growing dry-season crops and to develop decision support systems for those crops.

Aim/Purpose: This paper investigates the changing paradigms for technical skills that are needed by Data Engineers in 2018. Background: A decade ago, data engineers needed technical skills for Relational Database Management Systems (RDBMS), such as Oracle and Microsoft SQL Server. With the advent of Hadoop and NoSQL Databases in recent years, Data Engineers require new skills to support the large distributed datastores (Big Data) that currently exist. Job demand for Data Scientists and Data Engineers has increased over the last five years. Methodology: This research methodology leveraged the Pig programming language that used MapReduce software located on the Amazon Web Services (AWS) Cloud. Data was collected from 100 Indeed.com job advertisements during July of 2017 and then was uploaded to the AWS Cloud. Using MapReduce, phrases/words were counted and then sorted. The sorted phrase / word counts were then leveraged to create the list of the 20 top skills needed by a Data Engineer based on the job advertisements. This list was compared to the 20 top skills for a Data Engineer presented by Stitch that surveyed 6,500 Data Engineers in 2016. Contribution: This paper presents a list of the 20 top technical skills required by a Data Engineer.

Aim/Purpose. The aim of this study is to propose a teaching approach based on AI-based chatbot agents and to determine whether the use of this approach increases the students’ motivation. Background. Today, chatbots are an integral part of students’ lives where they are used in various contexts. Therefore, we are interested in incorporating these tools into our teaching process in order to profit from their benefits, assist and guide students while working with to prevent issues such as plagiarism and mainly to boost students’ motivation. Methodology. Using the proposed approach, new chatbot based learning activities were de-signed in three different courses for computer science engineering students. A mixed-method experimental study was conducted to evaluate students’ impression and satisfaction. Survey results of the students (N=58) who participated in the experiment (experimental group) were compared to the results of the students from the control group (N=60). Contribution. Trending AI conversational agents can be engaged in daily teaching activities as a learning assistant and coach to boost students motivation and skills development. Findings. Our study focuses on the impact of chatbots on student’s motivation. The study aimed to analyze the benefits and drawbacks associated with these conversational chatbots. Our findings revealed the significant role that chatbots can play in enhancing student motivation and improving teaching practices.

Knowledge management and knowledge assets have gained much prominence in recent years and are said to improve organizational performance. Knowledge capture and acquisition mechanisms enhance organizational memory and performance. However, knowledge capture and acquisition mechanisms in higher education institutions are not well known. The aim of this study was to investigate the knowledge capture and acquisition mechanisms at Kisii University. This was a case study in which data were collected through interviews and questionnaires. Purposive sampling was used to determine interview participants while questionnaire respondents were selected through stratified random sampling. Qualitative and quantitative data were analysed using SPSS® student version 14; it revealed that there were various knowledge capture and acquisition mechanisms at Kisii University. It was also established that the University encountered various challenges in knowledge capture and acquisition and lacked some essential knowledge capture and acquisition mechanisms. In this regard, this study proposed knowledge capture and acquisition guidelines that may be adopted by the University to enhance its organizational memory and performance.

It can be argued that public organizations, in order to provide the public with sufficient services in the current, highly competitive and continuously evolving environment, require changes. The changes that become necessary are often related to the implementation of information systems (IS). Moreover, when organizations are faced with changes, a change management (CM) process needs to be put in place. CM theories that are currently available to practitioners and academics are often contradictory; they mostly lack empirical evidence and are supported by unchallenged hypotheses concerning the nature of the contemporary CM. The aim of this paper is, therefore, to identify critical success factors (CFSs) for CM in IS projects. In order to reach this aim an explanation of changes in public organizations and the nature of CM are presented. Following this, a framework of CFSs for CM in IS projects are identified based on the literature review. The paper also examines two IS projects and uses them to demonstrate CFSs influencing CM in IS projects in Polish pubic organizations. A discussion of the research findings is provided and the paper concludes with a presentation of the study’s contributions and limitations as well as the stream of future work.

Aim/Purpose: This study investigates the factors that affect the post implementation success of a web-based learning management system at the University of Professional Studies, Accra (UPSA). Background: UPSA implemented an LMS to blend Web-based learning environment with the traditional methods of education to enable working students to acquire education. Methodology: An explanatory sequential mixed method was adopted, under the pragmatic paradigm, to investigate the level of acceptance of web-based learning by students. The effects of perceived usefulness, perceived ease of use, and other social factors were investigated. In all, 4500 final and third-year undergraduate students of UPSA made up the population. A sample size of 870 was used for this study. Contribution: This paper contributes to the body of knowledge by identifying the factors that hinder post-implementation of LMS at the tertiary level in Ghana and adds to the general literature available. Findings: The level of acceptance of LMS seems very low due to poor IT infrastructure, inadequate training, and the relevance of the system to quality lecture delivery. However, students’ intention to use LMS and the usefulness of LMS were perceived to be high, especially among students in higher levels. Recommendations for Practitioners: The authors recommend that IT infrastructure, especially reliable and fast internet connectivity, and adequate training should be provided. Recommendation for Researchers: Further research should be done to confirm if the provision of a more reliable internet system will boost students’ internet proficiency, which in turn will improve their utilisation of the LMS. Impact on Society: Help create awareness of schooling while pursuing a career and also improve interactions between students and lecturers. It will also improve enrolment and possibly reduce the cost of education in the long-run. Future Research: Researchers can look at the possibility of implementing total virtual learning systems at the tertiary level in Ghana.

Aim/Purpose: This study analyzes the mechanism of Internet capability (IC) driving knowledge creation performance (KCP). We consider the mediating role of strategic flexibility and the moderating role of informatization density. Background: The key to achieving KCP for firms is to transform knowledge created into new products or services and to realize the economic benefits. However, the research has not paid enough attention to firms’ KCP. Based on dynamic capability theory, this study empirically reveals how firms drive KCP through Internet capability. Methodology: The study uses survey data from 399 organizations in China. Through structural equation modeling, this study assesses the relationship between Internet capability, strategic flexibility, and KCP and uses hierarchical regression to test the moderating role of informatization density. Contribution: First, this study expands research on knowledge creation and focuses on the further achievement of knowledge creation performance. The study also enriches the exploration of KCP in the Internet context and deepens the research on the internal mechanism by which Internet capability influences KCP. Second, this study highlights the important role of informatization density in the Internet context and expands the research on the impact of external factors on the internal mechanism. Findings: First, Internet capability has a significantly positive effect on both strategic flexibility and KCP. Furthermore, Internet capability directly impacts strategic flexibility, yet it affects KCP both directly and indirectly through strategic flexibility, which confirms that strategic flexibility is a partial mediator in the relationship between Internet capability and KCP. Second, strategic flexibility positively influences KCP. Third, informatization density has a significant moderating effect on the relationship between Internet capability and KCP. Recommendations for Practitioners: The results indicate that firms should consider the importance of Internet capability and strategic flexibility for KCP in the Internet context. This study also provides a theoretical basis that could guide the Chinese government’s informatization construction of the industrial chain. Recommendation for Researchers: Researchers could further explore the role of other mediator variables (e.g., business process management, organizational agility) and consider the role of other moderator variables (e.g., resource commitment, learning orientation). Impact on Society: This study provides a reference for enterprises with similar cultural backgrounds in using Internet capability to enhance their competitive advantage. Future Research: Future research could collect data from various countries and regions to test the research model and conduct longitudinal studies to increase the robustness of the conclusions.

Aim/Purpose: This research aims to examine the role of Knowledge Management (KM) infrastructure (technological, structural, and cultural) in enhancing job satisfaction in the context of developing countries, as exemplified by Jordan. Background: Despite the presence of job satisfaction studies conducted in educational institutions across the world, knowledge management issues have not been taken into consideration as influencing factors. Methodology: A total of 168 responses to a questionnaire survey were collected from the academic staff at Zarqa University in Jordan. Multiple regression analysis was conducted to test the research hypotheses. Contribution: This study offers deeper understanding about the role that knowledge management infrastructure plays in enhancing job satisfaction from a developing country perspective. The proposed model is tested the first time in Jordan. Findings: Results of the current study revealed that there are significant positive impacts of technological and cultural KM infrastructures on job satisfaction, whereas structural KM infrastructure does not have a significant impact on job satisfaction. Also, the results revealed significant gender difference in perception of the impact of knowledge management infrastructure on job satisfaction. On the other hand, an ANOVA test found no significant difference in the impact of knowledge management infrastructure on job satisfaction among groups by age, experience, and academic rank. Recommendation for Researchers: Our findings can be used as a base of knowledge for further studies about knowledge management infrastructure and job satisfaction following different criteria and research procedures. Future Research: The current model can be applied and assessed further in other sectors, including public universities and other services sectors in developed and developing countries.

Aim/Purpose: This study aimed to investigate the impact of innovation management and learning orientation as the mechanisms playing the role of an intermediate relationship between entrepreneurial leadership and organisational performance of small and medium enterprises (SMEs) in Kuwait. Background: SMEs are currently among the principal economic instruments in most industrialised and developing countries. The contribution of SMEs can be viewed from various perspectives primarily related to the crucial role they play in developing entrepreneurial activities, employment generation, and improving innovativeness. Developing countries, including Kuwait and other countries, in the Gulf Cooperation Council (GCC), have recognised the key role played by SMEs as a strong pillar of growth. Consequently, many governments have formulated policies and programmes to facilitate the growth and success of SMEs. Unfortunately, the organisational performance of SMEs in developing countries, particularly in Kuwait, remains below expectations. The lagged growth could be due to a lack of good managerial practices and increasing competition that negatively impact their performance. Numerous researchers discovered the positive effect of entrepreneurial leadership on SMEs’ performance. However, a lack of clarity remains regarding the direct impact of entrepreneurial leadership on SMEs’ performance, especially in developing countries. Therefore, the nexus between entrepreneurial leadership and organisational performance is still indecisive and requires further studies. Methodology: This study adopted a quantitative approach based on a cross-sectional survey and descriptive design to gather data within a specific period. The data were collected by distributing a survey questionnaire to Kuwaiti SMEs’ owners and Chief Executive Officers (CEOs) via online and on-hand instruments. A total of 384 useable questionnaires were obtained. Moreover, the partial least square-structural equation modelling (PLS-SEM) analysis was performed to test the hypotheses. Contribution: The current study contributed to the existing literature by developing a moderated mediation model integrating entrepreneurial leadership, innovation management, and learning orientation. The study also investigated their effect on the organisational performance of SMEs. The study findings also bridged the existing significant literature gap regarding the role of these variables on SMEs’ performance in developing countries, particularly in Kuwait, due to the dearth of studies linking these variables in this context. Furthermore, this study empirically confirmed the significant effect of innovation management and learning orientation as intermediate variables in strengthening the relationship between entrepreneurial leadership and organisational performance in the settings of Kuwait SMEs, which has not been verified previously. Findings: The study findings showed the beneficial and significant impact of entrepreneurial leadership and innovation management on SME’s organisational performance. The relationship between entrepreneurial leadership and SMEs’ organisational performance is fundamentally mediated by innovation management and moderated by learning orientation. Recommendations for Practitioners: The present study provides valuable insights and information regarding the factors considered by the government, policymakers, SMEs’ stakeholders, and other authorities in the effort to increase the organisational performance level and facilitate the growth of SMEs in Kuwait. SMEs’ owners or CEOs should improve their awareness and knowledge of the importance of entrepreneurial leadership, innovation management, and learning orientation. These variables will have beneficial effects on the performance and assets to achieve success and sustainability if adopted and managed systematically. This study also recommends that SMEs’ entrepreneurs and top management should facilitate supportive culture by creating and maintaining an organisational climate and structure that encourages learning behaviour and innovation mindset among individuals. The initiative will motivate them towards acquiring, sharing, and utilising knowledge and increasing their ability to manage innovation systemically in all production processes to adapt to new technologies, practices, methods, and different circumstances. Recommendation for Researchers: The study findings highlighted the mediating effect of innovation management on the relationship between entrepreneurial leadership (the independent variable) and SMEs’ organisational performance (the dependent variable) and the moderating effect of learning orientation in the same nexus. These relationships were not extensively addressed in SMEs of developing countries and require further validation. Impact on Society: This study aims to influence the management strategies and practices adopted by entrepreneurs and policymakers who work in SMEs in developing countries. The effect will be reflected in the development of their firms and the national economy in general. Future Research: Future research should investigate the conceptual research framework against the backdrop of other developing economies and in other business settings to generalise the results. Future investigation should seek to establish the effect of entrepreneurial leadership style on other mechanisms, such as knowledge management processes, which could function with entrepreneurial leadership to improve SMEs’ performance efficiently. In addition, future studies may include middle and lower-level managers and employees, leading to more positive outcomes.

Aim/Purpose: Mobile commerce adoption is low in developing countries; hence, public servants may not consider mobile commerce and mobile payments. Understanding the factors that influence mobile commerce and mobile payments in their context will aid in promoting those services. Background: The study investigates the factors that influence public servants’ mobile commerce and mobile payments in Ghana. Hence, it provides some understanding of the various aspects of mobile commerce and mobile payments adoption, such as acceptance, use, and eventual adoption into the user’s daily life, and how that affects their behaviour. Methodology: The research was conducted by surveying the factors influencing public servants’ adoption of mobile commerce and payments in Ghana. A cross-sectional survey was undertaken to put the research model to the test to measure the constructs and their relationships. Contribution: The study confirmed previous findings and created a new conceptual model for mobile commerce and mobile payment adoption and usage in the Ghanaian context. Findings: The variables of performance expectancy, trust, and facilitating conditions have a significant positive influence on behavioural intention. The factors of effort expectation and social influence have a significant negative impact. Price value and perceived reliability are latent variables that do not affect behavioural intention. Behavioural intention and facilitating conditions significantly influence the actual use behaviour of mobile commerce and mobile payment users. Recommendations for Practitioners: Mobile commerce is emerging as a new mode of transactions, with firms providing enabling platforms for users. Mobile commerce could become the most acceptable application for the next generation of mobile platform applications. This study offers insights into the fluidity of the mobile environment, with implications that spell out what will be effective mobile commerce services that will continue to be relevant. Mobile applications are attractive to people because they provide a better user experience. These mobile applications have been optimised to provide a fast, easy and delightful experience. Mobile commerce and mobile payment service providers can attract and retain more users if attention is paid to performance expectancy, trust, and facilitating conditions since they influence individuals’ decisions to adopt. Mobile technology is almost ubiquitous, influencing both online sales and in-store sales. With the right mobile commerce platform and features, businesses can expect to increase in-store and online sales, catering to a more extensive clientele. Mobile devices are the primary means that most customers use to look up information about products they see in stores, such as product reviews and pricing options. This study indicates that mobile commerce service providers can achieve a more extensive customer base by promoting performance expectancy, trust, and behavioural intentions. Recommendation for Researchers: Despite the numerous studies in the mobile commerce literature, few have used integrated models of perceived reliability, trust, and price value or methods to evaluate these factors in the emerging mobile commerce industry. Also, it combines mobile commerce and mobile payments, which very few that we know of have done. Impact on Society: Ghana is already in a cash-lite economy. Thus, the study is appropriate with the result of trust being a significant factor. It implies that people will begin using mobile commerce and mobile payments with a bit of drive to bring about this drive quickly. Future Research: Future research could further test the adapted model with moderating factors of age, gender, and education to delve deeper into the complexities of mobile commerce and mobile payments.

Aim/Purpose: To predict the change-proneness of software from the continuous evolution using machine learning methods. To identify when software changes become statistically significant and how metrics change. Background: Software evolution is the most time-consuming activity after a software release. Understanding evolution patterns aids in understanding post-release software activities. Many methodologies have been proposed to comprehend software evolution and growth. As a result, change prediction is critical for future software maintenance. Methodology: I propose using machine learning methods to predict change-prone classes. Classes that are expected to change in future releases were defined as change-prone. The previous release was only considered by the researchers to define change-proneness. In this study, I use the evolution of software to redefine change-proneness. Many snapshots of software were studied to determine when changes became statistically significant, and snapshots were taken biweekly. The research was validated by looking at the evolution of five large open-source systems. Contribution: In this study, I use the evolution of software to redefine change-proneness. The research was validated by looking at the evolution of five large open-source systems. Findings: Software metrics can measure the significance of evolution in software. In addition, metric values change within different periods and the significance of change should be considered for each metric separately. For five classifiers, change-proneness prediction models were trained on one snapshot and tested on the next. In most snapshots, the prediction performance was excellent. For example, for Eclipse, the F-measure values were between 80 and 94. For other systems, the F-measure values were higher than 75 for most snapshots. Recommendations for Practitioners: Software change happens frequently in the evolution of software; however, the significance of change happens over a considerable length of time and this time should be considered when evaluating the quality of software. Recommendation for Researchers: Researchers should consider the significance of change when studying software evolution. Software changes should be taken from different perspectives besides the size or length of the code. Impact on Society: Software quality management is affected by the continuous evolution of projects. Knowing the appropriate time for software maintenance reduces the costs and impacts of software changes. Future Research: Studying the significance of software evolution for software refactoring helps improve the internal quality of software code.

Aim/Purpose: Based on the stimulus-organism-response (SOR) model, the current study investigated social commerce functions as an innovative retailing technological support by selecting the three most appropriate features for the Chinese online shopping environment with respective value co-creation intentions. Background: Social commerce is the customers’ online shopping touchpoint in the latest retail era, which serves as a corporate technological tool to extend specific customer services. Although social commerce is a relatively novel platform, limited theoretical attention was provided to determine retailers’ approaches in employing relevant functions to improve consumer experience and value co-creation. Methodology: A questionnaire was distributed to Chinese customers, with 408 valid questionnaires being returned and analyzed through Structural Equation Modeling (SEM). Contribution: The current study investigated the new retail concept and value co-creation from the consumer’s perspective by developing a theoretical model encompassing new retail traits and consumer value, which contributed to an alternative theoretical understanding of value creation, marketing, and consumer behaviour in the new retail business model. Findings: The results demonstrated that value co-creation intention was determined by customer experience, hedonic experience, and trust. Simultaneously, the three factors were significantly influenced by interactivity, personalisation, and sociability features. Specifically, customers’ perceptions of the new retail idea and the consumer co-creation value were examined. Resultantly, this study constructed a model bridging new retail characteristics with consumer value. Recommendations for Practitioners: Nonetheless, past new retail management practice studies mainly focused on superficial happiness in the process of human-computer interaction, which engendered a computer system design solely satisfying consumers’ sensory stimulation and experience while neglecting consumers’ hidden value demands. As such, a shift from the subjective perspective to the realisation perspective is required to express and further understand the actual meaning and depth of consumer happiness. Recommendation for Researchers: New retailers could incorporate social characteristics on social commerce platforms to improve the effectiveness of marketing strategies while increasing user trust to generate higher profitability. Impact on Society: The new retail enterprises should prioritise consumers’ acquisition of happiness meaning and deep experience through self-realisation, cognitive improvement, identity identification, and other aspects of consumer experiences and purchase processes. By accurately revealing and matching consumers’ fundamental perspectives, new retailers could continuously satisfy consumer requirements in optimally obtaining happiness. Future Research: Future comparative studies could be conducted on diverse companies within the same industry for comprehensive findings. Moreover, other underlying factors with significant influences, such as social convenience, group cognitive ability, individual family environment, and other external stimuli were not included in the present study examinations.

Aim/Purpose: This study presents a novel deep learning-based framework designed to enhance spontaneous micro-expression recognition by effectively increasing the amount and variety of data and balancing the class distribution to improve recognition accuracy. Background: Micro-expression recognition using deep learning requires large amounts of data. Micro-expression datasets are relatively small, and their class distribution is not balanced. Methodology: This study developed a framework using a deep learning-based model to recognize spontaneous micro-expressions on a person’s face. The framework also includes several technical stages, including image and data preprocessing. In data preprocessing, data augmentation is carried out to increase the amount and variety of data and class balancing to balance the distribution of sample classes in the dataset. Contribution: This study’s essential contribution lies in enhancing the accuracy of micro-expression recognition and overcoming the limited amount of data and imbalanced class distribution that typically leads to overfitting. Findings: The results indicate that the proposed framework, with its data preprocessing stages and deep learning model, significantly increases the accuracy of micro-expression recognition by overcoming dataset limitations and producing a balanced class distribution. This leads to improved micro-expression recognition accuracy using deep learning techniques. Recommendations for Practitioners: Practitioners can utilize the model produced by the proposed framework, which was developed to recognize spontaneous micro-expressions on a person’s face, by implementing it as an emotional analysis application based on facial micro-expressions. Recommendation for Researchers: Researchers involved in the development of a spontaneous micro-expression recognition framework for analyzing hidden emotions from a person’s face are playing an essential role in advancing this field and continue to search for more innovative deep learning-based solutions that continue to explore techniques to increase the amount and variety of data and find solutions to balancing the number of sample classes in various micro-expression datasets. They can further improvise to develop deep learning model architectures that are more suitable and relevant according to the needs of recognition tasks and the various characteristics of different datasets. Impact on Society: The proposed framework could significantly impact society by providing a reliable model for recognizing spontaneous micro-expressions in real-world applications, ranging from security systems and criminal investigations to healthcare and emotional analysis. Future Research: Developing a spontaneous micro-expression recognition framework based on spatial and temporal flow requires the learning model to classify optimal features. Our future work will focus more on exploring micro-expression features by developing various alternative learning models and increasing the weights of spatial and temporal features.

Aim/Purpose: This research aims to design a website-based group decision support system (DSS) user interface to support an integrated and sustainable waste management plan in Jagatera. The main focus of this research is to design a group DSS to help Jagatera prioritize several waste alternatives to be managed so that Jagatera can make the right decisions to serve the community. Background: The Indonesian government and various stakeholders are trying to solve the waste problem. Jagatera, as a waste recycling company, plays a role as a stakeholder in managing waste. In 2024, Jagatera plans to accept all waste types, which impacts the possibility of increasing waste management costs. If Jagatera does not have a waste management plan, this will impact reducing waste management services in the community. To solve this problem, the group DSS assists Jagatera in prioritizing waste based on aspects of waste management cost. Methodology: Jagatera, an Indonesian waste recycling company, is implementing a group DSS using the soft system methodology (SSM) method. The SSM process involves seven stages, including problem identification, problem explanation using rich pictures, system design, conceptual model design, real-life comparison, changes, and improvement steps. The final result is a prototype user interface design addressing the relationship between actors and the group DSS. The analytical hierarchy process (AHP) method prioritized waste based on management costs. This research obtained primary data from interviews with Jagatera management, a literature review regarding the group DSS, and questionnaires to determine the type of waste and evaluate user interface design. Contribution: This research focuses on determining waste handling priorities based on their management. It contributes the DSS, which uses a decision-making approach based on management groups developed using the SSM and AHP methods focused on waste management decisions. It also contributes to the availability of a user interface design from the DSS group that explains the interactions between actors. The implications of the availability of DSS groups in waste recycling companies can help management understand waste prioritization problems in a structured manner, increase decision-making efficiency, and impact better-quality waste management. Combining qualitative approaches from SSM to comprehend issues from different actor perspectives and AHP to assist quantitative methods in prioritizing decisions can yield theoretical implications when using the SSM and AHP methods together. Findings: This research produces a website-based group DSS user interface design that can facilitate decision-making using AHP techniques. The user interface design from the DSS group was developed using the SSM approach to identify complex problems at waste recycling companies in Indonesia. This study also evaluated the group DSS user interface design, which resulted in a score of 91.67%. This value means that the user interface design has met user expectations, which include functional, appearance, and comfort needs. These results also show that group DSS can enhance waste recycling companies’ decision-making process. The results of the AHP technique using all waste process information show that furniture waste, according to the CEO, is given more priority, and textile waste, according to the Managing Director. Group DSS developed using the AHP method allows user actors to provide decisions based on their perspectives and authority. Recommendations for Practitioners: This research shows that the availability of a group DSS is one of the digital transformation efforts that waste recycling companies can carry out to support the determination of a sustainable waste management plan. Managers benefit from DSS groups by providing a digital decision-making process to determine which types of waste should be prioritized based on management costs. Timely and complete information in the group DSS is helpful in the decision-making process and increases organizational knowledge based on the chosen strategy. Recommendation for Researchers: Developing a group DSS for waste recycling companies can encourage strategic decision-making processes. This research integrates SSM and AHP to support a comprehensive group DSS because SSM encourages a deeper and more detailed understanding of waste recycling companies with complex problems. At the same time, AHP provides a structured approach for recycling companies to make decisions. The group DSS that will be developed can be used to identify other more relevant criteria, such as environmental impact, waste management regulations, and technological capabilities. Apart from more varied criteria, the group DSS can be encouraged to provide various alternatives such as waste paper, metal, or glass. In addition to evaluating the group DSS’s user interface design, waste recycling companies need to consider training or support for users to increase system adoption. Impact on Society: The waste problem requires the role of various stakeholders, one of which is a waste recycling company. The availability of a group DSS design can guide waste recycling companies in providing efficient and effective services so that they can respond more quickly to the waste management needs of the community. The community also gets transparent information regarding their waste management. The impact of good group DSS is reducing the amount of waste in society. Future Research: Future research could identify various other types of waste used as alternatives in the decision-making process to illustrate the complexity of the prioritization process. Future research could also identify other criteria, such as environmental impact, social aspects of community involvement, or policy compliance. Future research could involve decision-makers from other parties, such as the government, who play an essential role in the waste industry.

Aim/Purpose: Accurate detection of vacant parking spaces is crucial for autonomous parking. Deep learning, particularly Graph Neural Networks (GNNs), holds promise for addressing the challenges of diverse parking lot appearances and complex visual environments. Our GNN-based approach leverages the spatial layout of detected marking points in around-view images to learn robust feature representations that are resilient to occlusions and lighting variations. We demonstrate significant accuracy improvements on benchmark datasets compared to existing methods, showcasing the effectiveness of our GNN-based solution. Further research is needed to explore the scalability and generalizability of this approach in real-world scenarios and to consider the potential ethical implications of autonomous parking technologies. Background: GNNs offer a number of advantages over traditional parking spot detection methods. Unlike methods that treat objects as discrete entities, GNNs may leverage the inherent connections among parking markers (lines, dots) inside an image. This ability to exploit spatial connections leads to more accurate parking space detection, even in challenging scenarios with shifting illumination. Real-time applications are another area where GNNs exhibit promise, which is critical for autonomous vehicles. Their ability to intuitively understand linkages across marking sites may further simplify the process compared to traditional deep-learning approaches that need complex feature development. Furthermore, the proposed GNN model streamlines parking space recognition by potentially combining slot inference and marking point recognition in a single step. All things considered, GNNs present a viable method for obtaining stronger and more precise parking slot recognition, opening the door for autonomous car self-parking technology developments. Methodology: The proposed research introduces a novel, end-to-end trainable method for parking slot detection using bird’s-eye images and GNNs. The approach involves a two-stage process. First, a marking-point detector network is employed to identify potential parking markers, extracting features such as confidence scores and positions. After refining these detections, a marking-point encoder network extracts and embeds location and appearance information. The enhanced data is then loaded into a fully linked network, with each node representing a marker. An attentional GNN is then utilized to leverage the spatial relationships between neighbors, allowing for selective information aggregation and capturing intricate interactions. Finally, a dedicated entrance line discriminator network, trained on GNN outputs, classifies pairs of markers as potential entry lines based on learned node attributes. This multi-stage approach, evaluated on benchmark datasets, aims to achieve robust and accurate parking slot detection even in diverse and challenging environments. Contribution: The present study makes a significant contribution to the parking slot detection domain by introducing an attentional GNN-based approach that capitalizes on the spatial relationships between marking points for enhanced robustness. Additionally, the paper offers a fully trainable end-to-end model that eliminates the need for manual post-processing, thereby streamlining the process. Furthermore, the study reduces training costs by dispensing with the need for detailed annotations of marking point properties, thereby making it more accessible and cost-effective. Findings: The goal of this research is to present a unique approach to parking space recognition using GNNs and bird’s-eye photos. The study’s findings demonstrated significant improvements over earlier algorithms, with accuracy on par with the state-of-the-art DMPR-PS method. Moreover, the suggested method provides a fully trainable solution with less reliance on manually specified rules and more economical training needs. One crucial component of this approach is the GNN’s performance. By making use of the spatial correlations between marking locations, the GNN delivers greater accuracy and recall than a completely linked baseline. The GNN successfully learns discriminative features by separating paired marking points (creating parking spots) from unpaired ones, according to further analysis using cosine similarity. There are restrictions, though, especially where there are unclear markings. Successful parking slot identification in various circumstances proves the recommended method’s usefulness, with occasional failures in poor visibility conditions. Future work addresses these limitations and explores adapting the model to different image formats (e.g., side-view) and scenarios without relying on prior entry line information. An ablation study is conducted to investigate the impact of different backbone architectures on image feature extraction. The results reveal that VGG16 is optimal for balancing accuracy and real-time processing requirements. Recommendations for Practitioners: Developers of parking systems are encouraged to incorporate GNN-based techniques into their autonomous parking systems, as these methods exhibit enhanced accuracy and robustness when handling a wide range of parking scenarios. Furthermore, attention mechanisms within deep learning models can provide significant advantages for tasks that involve spatial relationships and contextual information in other vision-based applications. Recommendation for Researchers: Further research is necessary to assess the effectiveness of GNN-based methods in real-world situations. To obtain accurate results, it is important to employ large-scale datasets that include diverse lighting conditions, parking layouts, and vehicle types. Incorporating semantic information such as parking signs and lane markings into GNN models can enhance their ability to interpret and understand context. Moreover, it is crucial to address ethical concerns, including privacy, potential biases, and responsible deployment, in the development of autonomous parking technologies. Impact on Society: Optimized utilization of parking spaces can help cities manage parking resources efficiently, thereby reducing traffic congestion and fuel consumption. Automating parking processes can also enhance accessibility and provide safer and more convenient parking experiences, especially for individuals with disabilities. The development of dependable parking capabilities for autonomous vehicles can also contribute to smoother traffic flow, potentially reducing accidents and positively impacting society. Future Research: Developing and optimizing graph neural network-based models for real-time deployment in autonomous vehicles with limited resources is a critical objective. Investigating the integration of GNNs with other deep learning techniques for multi-modal parking slot detection, radar, and other sensors is essential for enhancing the understanding of the environment. Lastly, it is crucial to develop explainable AI methods to elucidate the decision-making processes of GNN models in parking slot detection, ensuring fairness, transparency, and responsible utilization of this technology.

Aim/Purpose: This research investigated the determinant factors influencing the adoption intentions of Chatsicum, a Knowledge-Based Chatbot (KBC) aimed at enhancing the species literacy of biodiversity students. Background: This research was conducted to bridge the gap between technology, education, and biodiversity conservation. Innovative solutions are needed to empower individuals with knowledge, particularly species knowledge, in preserving the natural world. Methodology: The study employed a quantitative approach using the Partial Least Square Structural Equation Modeling (PLS-SEM) and sampled 145 university students as respondents. The research model combined the Task-Technology Fit (TTF) framework with elements from the Diffusion of Innovation (DOI), including relative advantage, compatibility, complexity, and observability. Also, the model introduced perceived trust as an independent variable. The primary dependent variable under examination was the intention to use the KBC. Contribution: The findings of this research contribute to a deeper understanding of the critical factors affecting the adoption of the KBC in biodiversity education and outreach, as studies in this context are limited. This study provides valuable insights for developers, educators, and policymakers interested in promoting species literacy and leveraging innovative technologies by analyzing the interplay of TTF and DOI constructs alongside perceived trust. Ultimately, this research aims to foster more effective and accessible biodiversity education strategies. Findings: TTF influenced all DOI variables, such as relative advantage, compatibility, observability, and trust positively and complexity negatively. In conclusion, TTF strongly affected usage intention indirectly. However, relative advantage, complexity, and observability insignificantly influenced the intention to use. Meanwhile, compatibility and trust strongly affected the use intention. Recommendations for Practitioners: Developers should prioritize building and maintaining chatbots that are aligned with the tasks, needs, and goals of the target users, as well as establishing trust through the assurance of information accuracy. Educators could develop tailored educational interventions that resonate with the values and preferences of diverse learners and are aligned closely with students’ learning needs, preferences, and curriculum while ensuring seamless integration with the existing educational context. Conservation organizations and policymakers could also utilize the findings of this study to enhance their outreach strategies, as the KBC is intended for students and biodiversity laypeople. Recommendation for Researchers: Researchers should explore the nuances of relationships between TTF and DOI, as well as trust, and consider the potential influence of mediating and moderating variables to advance the field of technology adoption in educational contexts. Researchers could also explore why relative advantage, complexity, and observability did not significantly impact the usage intention and whether specific user segments or contextual factors influence these relationships. Impact on Society: This research has significant societal impacts by improving species literacy, advancing technology in education, and promoting conservation efforts. Species knowledge could raise awareness regarding biodiversity and the importance of conservation, thereby leading to more informed and responsible citizens. Future Research: Future works should address the challenges and opportunities presented by KBCs in the context of species literacy enhancement, for example, interventions or experiments to influence the non-significant factors. Furthermore, longitudinal studies should investigate whether user behavior evolves. Ultimately, examining the correlation between species literacy, specifically when augmented by chatbots, and tangible conservation practices is an imperative domain in the future. It may entail evaluating the extent to which enhanced knowledge leads to concrete measures promoting biodiversity preservation.

Recently, interest in the correlation between 'contract' in transaction governance and 'trust' in relational governance mechanisms has been growing. This study focuses on issues related to the evolution of contract and inter-organisational trust dynamics in transaction governance and uses mixed research method to investigate sectors related to transaction governance in Taiwan's electronics industry. The study finds higher flexibility in contract implementation to be a promoter of trust between two parties in a relationship, thereby promoting project execution efficiency in the case of Taiwanese firms. Organisational management differs between the East and West; therefore, Western firms should understand how various contractual provisions can be used to accommodate different transactions when cooperating with Taiwanese electronics companies.

This study investigates cross-border commercial air passenger traffic in Africa, focusing on the development of the 15 busiest country pairs during the period 1989 to 2015. It explores dimensions not previously studied by using ICAO's 'Traffic by Flight Stage' (TFS) and data from the CEPII Gravity Dataset. The spatial results show on an uneven geographical distribution of country pairs with the centre of gravity to South, East and North-East Africa, with one long-distance corridor between Egypt and South Africa. Countries in North and West Africa have rather few linkages, except for Egypt. Central African countries are not represented among the 15 country pairs. Although the number of passengers and the rank among the countries have shifted, South Africa and Egypt stand out, as having most country pair connections. Factors such as changing economic, diplomatic and political relations have had an influence on changing country pair connections throughout the period. A number of variables were selected to investigate how they correlated with Africa's commercial passenger traffic. Of the seven variables selected, five did show on a correlation and two did partly so. In that view, Africa's air traffic follows rather typical patterns.

Transforming a school from traditional teaching and learning to a one-to-one (1:1) classroom, in which a teacher and students have personal digital devices, inevitably requires changes in the way the teacher addresses her role. This study examined the implications of integrating 1:1 computing on teachers’ pedagogical perceptions and the classroom’s educational discourse. A change in pedagogical perceptions during three years of teaching within this model was investigated. The research analyzed data from 14 teachers teaching in a junior high school in the north of Israel collected over the course of three years through interviews and lesson observations. The findings show that the 1:1 computing allows teachers to improve their teaching skills; however, it fails to change their fundamental attitudes in regard to teaching and learning processes. It was further found that the use of a laptop by each student does not significantly improve the classroom’s learning discourse. The computer is perceived as an individual or group learning technology rather than as a tool for conducting learning discourse. An analysis of the data collected shows a great contribution to collaboration among teachers in preparing technology-enhanced lessons. The findings are discussed in terms of Bruner’s (Olson & Bruner, 1996) “folk psychology” and “folk pedagogy” of teachers and “the new learning ecology” framework in 1:1 classroom (Lee, Spires, Wiebe, Hollebrands, & Young, 2015). One of the main recommendations of this research is to reflect on findings from the teaching staff and the school community emphasizing 1:1 technology as a tool for significant pedagogical change. It seems that the use of personal technology per se is not enough for pedagogical changes to take place; the change must begin with teachers’ perceptions and attitudes.

Implementing inquiry in the outdoors introduces many challenges for teachers, some of which can be dealt with using mobile technologies. For productive use of these technologies, teachers should be provided with the opportunity to develop relevant knowledge and practices. In a professional development (PD) program in this design-based research, 24 teachers were involved in adaptation of a learning environment supporting inquiry in the outdoors that included the use of mobile technologies. They first experienced the learning environment as learners, then adapted it for their own use, and finally, enacted the adapted environment with peers. We examined the scope and character of teacher involvement in adaptation, and the consequent professional growth, by analyzing observations, questionnaires, interviews and the adapted learning-environments. Findings indicate that all teachers demonstrated change processes, including changes in knowledge and practice, but the coherence of the learning environments decreased when substantial adaptations were made. Some teachers demonstrated professional growth, as reflected by their implementation of ideas learned in the PD program in their daily practice, long after the PD program had ended. This study demonstrates how the Teachers as Designers approach can support teacher learning and illustrates productive use of scaffolds for teacher growth and professional development.

There is a growing interest in the assessment of tangible skills and competence. Specifically, there is an increase in the offerings of competency-based assessments, and some academic institutions are offering college credits for individuals who can demonstrate adequate level of competency on such assessments. An increased interest has been placed on competency-based computer simulations that can assist learners to gain tangible skills. While computer simulations and competency-based projects, in general and particularly in management, have demonstrated great value, there are still limited empirical results on their benefits to e-learners. Thus, we have developed a quasi-experimental research, using a survey instrument on pre- and post-tests, to collect the set of 12 management skills from e-learners attending courses that included both competency-based computer simulations and those that didn’t. Our data included a total of 253 participants. Results show that all 12 management skills measures demonstrated very high reliability. Our results also indicate that all 12 skills of the competency-based computer simulations had higher increase than those that didn’t. Analyses on the mean increases indicated an overall statistically significant difference for six of the 12 management skills enhancements between the experimental and control groups. Our findings demonstrate that overall computer simulations and competency-based projects do provide added value in the context of e-learning when it comes to management skills.

Creative computing is one of the rapidly growing educational trends around the world. Previous studies have shown that creative computing can empower disadvantaged children and youth. At-risk youth tend to hold a negative view of self and perceive their abilities as inferior compared to “normative” pupils. The Implicit Theories of Intelligence approach (ITI; Dweck, 1999, 2008) suggests a way of changing beliefs regarding one’s abilities. This paper reports findings from an experiment that explores the impact of a short intervention among at-risk youth and “normative” high-school students on (1) changing ITI from being perceived as fixed (entity view of intelligence) to more flexible (incremental view of intelligence) and (2) the quality of digital self-representations programmed though a creative computing app. The participants were 117 Israeli youth aged 14-17, half of whom were at-risk youth. The participants were randomly assigned to the experimental and control conditions. The experimental group watched a video of a lecture regarding brain plasticity that emphasized flexibility and the potential of human intelligence to be cultivated. The control group watched a neutral lecture about brain-functioning and creativity. Following the intervention, all of the participants watched screencasts of basic training for the Scratch programming app, designed artifacts that digitally represented themselves five years later and reported their ITI. The results showed more incremental ITI in the experimental group compared to the control group and among normative students compared to at-risk youth. In contrast to the research hypothesis, the Scratch projects of the at-risk youth, especially in the experimental condition, were rated by neutral judges as being more creative, more aesthetically designed, and more clearly conveying their message. The results suggest that creative computing combined with the ITI intervention is a way of developing creativity, especially among at-risk youth. Increasing the number of youths who hold incremental views of intelligence and developing computational thinking may contribute to their empowerment and well-being, improve learning and promote creativity.

As a result of the rapid development of Information and Communication Technology (ICT) and the growing interest in Internet-based tools for language classroom, it has become a pressing need for educators to locate, evaluate and select the most appropriate language-learning digital resources that foster more communicative and meaningful learning processes. Hence, this paper describes a mixed research project that, on the first hand, aimed at proposing a Checklist for evaluating language websites built on the principles of the Communicative Approach, and on the second hand, sought to strengthen the teachers’ Knowing-how-to-do skill as part of their digital competence. To achieve these goals, a four-phase research procedure was followed that included reviewing relevant literature and administering qualitative and quantitative research methods to participants (i.e., language teachers, an expert in the Computer-Assisted Language Learning (CALL) field and a college professor) in order to gain insights into problematic issues and, thereafter, to contribute to the creation and validation of the Checklist model and the Study Guide. The findings revealed that: (a) evaluating language websites leads to the enhancement of the teachers’ practical skills and their knowledge of the technological language; and (b) having an assessment instrument allows educators to choose the materials that best meet their communicative teaching purposes.

Aim/Purpose: Students face many challenges improving their soft skills such as critical thinking. This paper offers one possible solution to this problem. Background: This paper considers one method of enhancing critical thinking through a problem-solving game called the Coffee Shop. Problem-solving is a key component to critical thinking, and game-playing is one method of enhancing this through an interactive teaching method. Methodology: Three classes of Vietnamese high school students engaged in the Coffee Shop game. The method seeks outcome measurements through the use of analysis of multiple surveys to assess and interpret if critical thinking may have been improved. Contribution: The study may help to understand the importance of problem-solving in the context of an entrepreneurial setting and add to the variation of methods used to deliver the lesson to students in the classroom. Findings: The findings show that practicing problem-solving scenarios with a focus on critical thinking in a time limited setting results in a measured improvement of this skill. Recommendations for Practitioners: The findings suggest that educators could use games more as tools for problem-solving to contribute to their students’ learning outcomes around developing critical thinking. Recommendation for Researchers: More research could be devoted to developing problem-solving and critical thinking skills through game-play models. Impact on Society: Improved critical thinking skills in individuals could make a greater contribution to society. Future Research A comparative study between different high school grades and genders as well as between different countries or cultures.

Aim/Purpose: This article aimed to design and evaluate a pedagogical technique for altering students’ classroom digital multitasking behaviors. The technique we designed and evaluated is called course-based undergraduate research experience (CURE). With this technique, the students wrote a research article based on a multitasking experiment that the instructor conducted with the students. The students conducted a literature review, developed their own research questions, they analyzed experiment data, and presented results. This study evaluated the how the CURE contributed to student multitasking behavior change. Background: Multitasking is defined as doing more than one thing at a time. Multitasking is really the engagement in individual and discrete tasks that are performed in succession. Research showed that students multitasked very often during courses. Researchers indicated that this was a problem especially for online teaching, because when students went online, they tended to multitask. Extant research indicated that digital multitasking in class harmed student performance. Multiple studies suggested that students who multitasked spent more time finishing their tasks and made more mistakes. Regardless of students’ gender or GPA, students who multitasked in class performed worse and got a lower grade than those who did not. However, little is known about how to change students’ digital multitasking behaviors. In this study, we used the transtheoretical model of behavior change to investigate how our pedagogical technique (CURE) changed students’ digital multitasking behaviors. Methodology: Using a course-based undergraduate research experience design, a new classroom intervention was designed and evaluated through a content analysis of pre- and post-intervention student reflections. As part of the course-based undergraduate research experience design, the students conducted a literature review, developed their own research questions, they analyzed experiment data, and presented results. This study evaluated the how teaching using a course-based undergraduate research experience contributed to student multitasking behavior change. Transtheoretical model of behavior change was used to investigate how our pedagogical technique changed students’ digital multitasking behaviors. Contribution: The paper described how teaching using a course-based undergraduate research experience can be used in practice. Further, it demonstrated the utility of this technique in changing student digital multitasking behaviors. This study contributed to constructivist approaches in education. Other unwanted student attitudes and behaviors can be changed using this approach to learning. Findings: As a result of CURE teaching, a majority of students observed the negative aspects of multitasking and intended to change their digital multitasking behaviors. Sixty-one percent of the participants experienced attitude changes, namely increased negative attitude towards multitasking in class. This is important because research found that while both students and instructors believed off-task technology use hinders learning, their views differed significantly, with more instructors than students feeling strongly that students’ use of technology in class is a problem. Moreover, our study showed that with teaching using CURE, it is possible to move the students on the ladder of change as quickly as within one semester (13 weeks). Seventy-one percent of the students reported moving to a higher stage of change post-intervention. Recommendations for Practitioners: Faculty wishing to curb student digital multitasking behaviors may conduct in-class experimentation with multitasking and have their students write a research report on their findings. Course-based undergraduate research experiences may make the effects of digital multitasking more apparent to the students. The students may become more aware of their own multitasking behaviors rather than doing them habitually. This technique is also recommended for those instructors who would like to introduce academic careers as a potential career option to their students. Recommendation for Researchers: Researchers should explore changing other unwanted undergraduate student behaviors with course-based undergraduate experiences. Researchers may use the transtheoretical model of change to evaluate the effectiveness of techniques used to change behaviors. Impact on Society: The negative outcomes of digital multitasking are not confined to the classroom. Digital multitasking impacts productivity in many domains. If techniques such as those used in this article become more common, changes in multitasking intentions could show broad improvements in productivity across many fields. Future Research: This paper constitutes a pilot study due to the small convenience sample that is used for the study. Future research should replicate this study with larger and randomized samples. Further investigation of the CURE technique can improve its effectiveness or reduce the instructor input while attaining the same behavioral changes.