This paper proposes a method for predicting college students' performance based on learning behaviour data mining. The method addresses the issue of limited sample size affecting prediction accuracy. It utilises the K-means clustering algorithm to mine learning behaviour data and employs a density-based approach to determine optimal clustering centres, which are then output as the results of the clustering process. These clustering results are used as input for an attention encoder-decoder model to extract features from the learning behaviour sequence, incorporating an attention mechanism, sequence feature generator, and decoder. The characteristics derived from the learning behaviour sequence are then used to establish a prediction model for college students' performance, employing support vector regression. Experimental results demonstrate that this method accurately predicts students' performance with a relative error of less than 4% by leveraging the results obtained from learning behaviour data mining.

Dynamic nature of the FMCG sector perpetually provides a tricky challenge for organisational leaders to nurture their employees. High demand for products, less shelf life and tough competitors always challenge the leaders to uphold their products in the market. Due to technology and e-commerce, many new competitors have joined the market, vying with the industry's veterans. Due to their unique business models that match client needs, these firms are expected to boost FMCG industry income in the future. Managers' leadership styles depend primarily on emotional intelligence. This quantitative study examines how emotional intelligence influences West Bengal FMCG senior managers' leadership styles. 500 FMCG managers were selected. PLS-SEM is used to study. Emotionally competent leaders choose transactional and transformational leadership styles depending on the occasion. Managers' transactional leadership style is strongly influenced by their sympathetic awareness, as shown by a path coefficient of 0.755. Transformational leadership style has a path coefficient of 0.693, indicating that managers' empathy affects their organisational management. Thus, sympathetic awareness and emotion regulation predict good management leadership.

In order to improve the standardisation of mutual information index, accuracy rate and recall rate of student classroom behaviour recognition method, this paper proposes a student's classroom behaviour recognition method based on abstract hidden Markov model (HMM). After cleaning the students' classroom behaviour data, improve the data quality through interpolation and standardisation, and then divide the types of students' classroom behaviour. Then, in support vector machine, abstract HMM is used to calculate the output probability density of support vector machine. Finally, according to the characteristic interval of classroom behaviour, we can judge the category of behaviour characteristics. The experiment shows that normalised mutual information (NMI) index of this method is closer to one, and the maximum AUC-PR index can reach 0.82, which shows that this method can identify students' classroom behaviour more effectively and reliably.

In this article, we have attempted to study the ways in which the COVID-19 pandemic has gradually increased and impacted the world. The authors integrate the knowledge from cognitive psychology literature to illustrate how the limitations of the human mind might have a critical role in the decisions taken during the COVID-19 pandemic. The authors show the correlation between different biases in various contexts involved in the COVID-19 pandemic and highlight the ways in which we can nudge ourselves and various stakeholders involved in the decision-making process. This study uses a typology of biases to examine how different patterns of biases affect the decision-making behaviour of people during the pandemic. The presented model investigates the potential interrelations among environmental transformations, cognitive biases, and strategic decisions. By referring to cognitive biases, our model also helps to understand why the same performance improvement practices might incite different opinions among decision-makers.

Table of Contents for IISIT Volume 16, 2019

Aim/Purpose: In the midst of COVID-19, classes are transitioned online. Instructors and students scramble for ways to adapt to this change. This paper shares an experience of one instructor in how he has gone through the adaptation. Background: This section provides a contextual background of online teaching. The instructor made use of M-learning to support his online teaching and adopted the UTAUT model to guide his interpretation of the phenomenon. Methodology: The methodology used in this study is action research through participant-observation. The instructor was able to look at his own practice in teaching and reflect on it through the lens of the UTAUT conceptual frame-work. Contribution: The results helped the instructor improve his practice and better under-stand his educational situations. From the narrative, others can adapt and use various apps and platforms as well as follow the processes to teach online. Findings: This study shares an experience of how one instructor had figured out ways to use M-learning tools to make the online teaching and learning more feasible and engaging. It points out ways that the instructor could connect meaningfully with his students through the various apps and plat-forms. Recommendations for Practitioners: The social aspects of learning are indispensable whether it takes place in person or online. Students need opportunities to connect socially; there-fore, instructors should try to optimize technology use to create such opportunities for conducive learning. Recommendations for Researchers: Quantitative studies using surveys or quasi-experiment methods should be the next step. Validated inventories with measures can be adopted and used in these studies. Statistical analysis can be applied to derive more objective findings. Impact on Society: Online teaching emerges as a solution for the delivery of education in the midst of COVID-19, but more studies are needed to overcome obstacles and barriers to both instructors and students. Future Research: Future studies should look at the obstacles that instructors encounter and the barriers with technology access and inequalities that students face in online classes.

Aim/Purpose: This study examined learning during the COVID-19 crisis, as perceived by preservice teachers at the time of their academic studies and their student teaching experience. Background: The COVID-19 crisis is unexpected. On one hand, it disrupted learning in all learning frameworks, on the other, it may create a change in learning characteristics even after the end of the crisis. This study examined the pro-ductive, challenging, and thwarting factors that preservice teachers encountered during their studies and in the course of their student teaching during the COVID-19 period, from the perspective of preservice teachers. Methodology: The study involved 287 students studying at teacher training institutions in Israel. The preservice teachers were studying online, and in addition experienced online teaching of students in schools, guided by their own teacher. The study used a mixed method. The questionnaire included closed and open questions. The data were collected in 2020. Contribution: Identifying the affecting factors may deepen the understanding of online learning/teaching and assist in the optimal implementation of online learning. Findings: Online learning experience. We found that some of the lessons at institutions of higher learning were delivered in the format of online lectures. Many pre-service teachers had difficulty sitting in front of a computer for many hours—“Zoom fatigue.” Preservice teachers who had difficulty self-regulating and self-mobilizing for study, experienced accumulating loads, which caused them feelings of stress and anxiety. The word count indicated that the words that appeared most often were “load” and “stress.” Some preservice teachers wrote that collaborating in forums with others made it easier for them. Some suggested diversifying by digital means, incorporating asynchronous units and illustrative films, and easing up on online lectures, as a substitute for face-to-face lectures. Online teaching experience in schools. The preservice teachers' descriptions show that in lessons taught in the format of lectures and communication of content, there were discipline problems and non-learning. According to the preservice teachers, discipline problems stemmed from difficulties concentrating, physical distance, load, and failure to address the students' difficulties. Recommendations for Practitioners: In choosing schools for student teaching, it is recommended to reach an understanding with the school about the online learning policy and organization. It is important to hold synchronous sessions in small groups of 5 to 10 students. The sessions should focus on the mental wellbeing of the students, and on the acquisition of knowledge and skills. Students should be prepared for participation in asynchronous digital lessons, which should be produced by professionals. It should be remembered that the change of medium from face-to-face to online learning also changes the familiar learning environment for all parties and requires modifying the ways of teaching. Recommendations for Researchers: A change in the learning medium also requires a change in the definition of objectives and goals expected of each party—students, teachers, and parents. All parties must learn to view online learning as a method that enables empowerment and the application of 21st century skills. Impact on Society: Teachers' ability to deploy 21st century skills in an online environment de-pends largely on their experience, knowledge, skills, and attitude toward these skills. Future Research: This study examined the issue from the perspective of preservice teachers. It is recommended to examine it also from the perspective of teachers and students.

Table of Contents for IISIT Volume 19, 2022

Table of Contents for IISIT Volume 19, 2022

Aim/Purpose. The study aimed to examine the remote and face-to-face experience of pedagogical training in kindergarten after the third COVID-19 closure in Israel. Background. The outbreak of the COVID-19 epidemic in 2020 changed the training system, and preservice teachers were required to have their practical experience in the kindergartens both remotely and face-to-face. They had to adapt to the new requirements of teacher training programs and receive professional coaching and support from the pedagogical instructor remotely. Methodology. The sample comprised 26 early childhood preservice teachers, who received academic training that includes proficiency in digital technology. The data were collected through feedback that they wrote themselves during the training period and analyzed in the interpretive approach. Contribution. The contribution of the present study is that it examines the pedagogical coaching from the perspective of preservice teachers in a kindergarten during the COVID-19 epidemic, which forced a transition from face-to-face to remote pedagogical training, then back to face-to-face pedagogical instruction. To the best of my knowledge, no such study has been carried out to date, which makes it unique. Findings. The main findings indicate the dissatisfaction of most preservice kindergarten teachers with the remote pedagogical training (about 85%) at the physical, emotional, technological, and pedagogical levels, and the satisfaction of most preservice kindergarten teachers with face-to-face pedagogical training (about 92%) at the physical, emotional, and pedagogical levels. The main conclusion is that technology is a potential barrier in training, and that preservice kindergarten teachers need a pedagogical instructor present at a professional face-to-face meeting. Recommendations for Practitioners. The findings of the study show how important in-person learning and engagement is for everyone especially for Preservice teachers’ and may be helpful for pedagogical coaching teams. Recommendations for Researchers. Preservice teachers’ awareness of the pedagogical coaching experiences could persuade the coaching teams to avoid potential difficulties, increase emotional support, and refine the use of technology to make it a closer substitute for frontal communication. Impact on Society. Face-to-face training based on interpersonal relationship, allows to develop better during the training period.

Aim/Purpose: The paper’s objective is to examine the challenges of using the mobile phone to mine location data for effective contact tracing of symptomatic, pre-symptomatic, and asymptomatic individuals and the implications of this technology for public health governance. Background: The COVID-19 crisis has created an unprecedented need for contact tracing across South Africa, requiring thousands of people to be traced and their details captured in government health databases as part of public health efforts aimed at breaking the chains of transmission. Contact tracing for COVID-19 requires the identification of persons who may have been exposed to the virus and following them up daily for 14 days from the last point of exposure. Mining mobile phone location data can play a critical role in locating people from the time they were identified as contacts to the time they access medical assistance. In this case, it aids data flow to various databases designated for COVID-19 work. Methodology: The researchers conducted a review of the available literature on this subject drawing from academic articles published in peer-reviewed journals, research reports, and other relevant national and international government documents reporting on public health and COVID-19. Document analysis was used as the primary research method, drawing on the case studies. Contribution: Contact tracing remains a critical strategy in curbing the deadly COVID-19 pandemic in South Africa and elsewhere in the world. However, given increasing concern regarding its invasive nature and possible infringement of individual liberties, it is imperative to interrogate the challenges related to its implementation to ensure a balance with public governance. The research findings can thus be used to inform policies and practices associated with contact tracing in South Africa. Findings: The study found that contact tracing using mobile phone location data mining can be used to enforce quarantine measures such as lockdowns aimed at mitigating a public health emergency such as COVID-19. However, the use of technology can expose the public to criminal activities by exposing their locations. From a public governance point of view, any exposure of the public to social ills is highly undesirable. Recommendations for Practitioners: In using contact tracing apps to provide pertinent data location caution needs to be exercised to ensure that sensitive private information is not made public to the extent that it compromises citizens’ safety and security. The study recommends the development and implementation of data use protocols to support the use of this technology, in order to mitigate against infringement of individual privacy and other civil liberties. Recommendation for Researchers: Researchers should explore ways of improving digital applications in order to improve the acceptability of the use of contact tracing technology to manage pandemics such as COVID-19, paying attention to ethical considerations. Impact on Society: Since contact tracing has implications for privacy and confidentiality it must be conducted with caution. This research highlights the challenges that the authorities must address to ensure that the right to privacy and confidentiality is upheld. Future Research: Future research could focus on collecting primary data to provide insight on contact tracing through mining mobile phone location data. Research could also be conducted on how app-based technology can enhance the effectiveness of contact tracing in order to optimize testing and tracing coverage. This has the potential to minimize transmission whilst also minimizing tracing delays. Moreover, it is important to develop contact tracing apps that are universally inter-operable and privacy-preserving.

Aim/Purpose: This paper aims to analyze the availability and pricing of perishable farm produce before and during the lockdown restrictions imposed due to Covid-19. This paper also proposes machine learning and deep learning models to help the farmers decide on an appropriate market to sell their farm produce and get a fair price for their product. Background: Developing countries like India have regulated agricultural markets governed by country-specific protective laws like the Essential Commodities Act and the Agricultural Produce Market Committee (APMC) Act. These regulations restrict the sale of agricultural produce to a predefined set of local markets. Covid-19 pandemic led to a lockdown during the first half of 2020 which resulted in supply disruption and demand-supply mismatch of agricultural commodities at these local markets. These demand-supply dynamics led to disruptions in the pricing of the farm produce leading to a lower price realization for farmers. Hence it is essential to analyze the impact of this disruption on the pricing of farm produce at a granular level. Moreover, the farmers need a tool that guides them with the most suitable market/city/town to sell their farm produce to get a fair price. Methodology: One hundred and fifty thousand samples from the agricultural dataset, released by the Government of India, were used to perform statistical analysis and identify the supply disruptions as well as price disruptions of perishable agricultural produce. In addition, more than seventeen thousand samples were used to implement and train machine learning and deep learning models that can predict and guide the farmers about the appropriate market to sell their farm produce. In essence, the paper uses descriptive analytics to analyze the impact of COVID-19 on agricultural produce pricing. The paper explores the usage of prescriptive analytics to recommend an appropriate market to sell agricultural produce. Contribution: Five machine learning models based on Logistic Regression, K-Nearest Neighbors, Support Vector Machine, Random Forest, and Gradient Boosting, and three deep learning models based on Artificial Neural Networks were implemented. The performance of these models was compared using metrics like Precision, Recall, Accuracy, and F1-Score. Findings: Among the five classification models, the Gradient Boosting classifier was the optimal classifier that achieved precision, recall, accuracy, and F1 score of 99%. Out of the three deep learning models, the Adam optimizer-based deep neural network achieved precision, recall, accuracy, and F1 score of 99%. Recommendations for Practitioners: Gradient boosting technique and Adam-based deep learning model should be the preferred choice for analyzing agricultural pricing-related problems. Recommendation for Researchers: Ensemble learning techniques like Random Forest and Gradient boosting perform better than non-Ensemble classification techniques. Hyperparameter tuning is an essential step in developing these models and it improves the performance of the model. Impact on Society: Statistical analysis of the data revealed the true nature of demand and supply and price disruption. This analysis helps to assess the revenue impact borne by the farmers due to Covid-19. The machine learning and deep learning models help the farmers to get a better price for their crops. Though the da-taset used in this paper is related to India, the outcome of this research work applies to many developing countries that have similar regulated markets. Hence farmers from developing countries across the world can benefit from the outcome of this research work. Future Research: The machine learning and deep learning models were implemented and tested for markets in and around Bangalore. The model can be expanded to cover other markets within India.

Aim/Purpose: ************************************************************************ After its investigation, the Research Ethics, Integrity, and Governance team at RMIT University found that the primary author of this paper breached the Australian Code and/or RMIT Policy and requested that the article be retracted. ************************************************************************** This paper aimed to examine the influence of ethical and transformational leadership on employee creativity in Malaysia’s private higher education institutions (PHEIs) and the mediating role of organizational citizenship behavior. Background: To ensure their survival and success in today’s market, organizations need people who are creative and driven. Previous studies have demonstrated the importance of ethical leadership in fostering employee innovation and good corporate responsibility. Research on ethical leadership and transformational leadership, in particular, has played a significant role in elucidating the role of leadership in relation to organizational citizenship behavior (OCB). In this study, we have focused on ethical and transformational leadership as an antecedent for enhancing employee creativity. Despite an increase in leadership research, little is known about the underlying mechanisms that link ethical leadership and transformational leadership to OCB. Because it sheds light on factors other than ethical leadership and transformational leadership that influence employees’ extra-role activity, this research is relevant theoretically. OCB may have a mediating function between ethical leadership and transformational leadership style and employee creativity because it is associated with the greatest outcomes, but empirical research has yet to prove this. So, one of the study’s goals is to add to the hypotheses about how ethical leadership style and transformational leadership affect employee creativity by using an important mediating variable – OCB. Methodology: This study adopted a quantitative approach based on a cross-sectional survey and descriptive design to gather the data in a specific period. A convenient sampling approach was used to gauge 275 employees from Malaysia’s PHEIs. To test the hypotheses and obtain a conclusion, the acquired data was analyzed using the partial least square technique (PLS-SEM). Contribution: The study contributes to leadership literature by advancing OCB as a mediating factor that accounts for the link between ethical and transformational leadership and employee creativity in the higher education sector. Findings: According to the research, OCB has a substantial influence on the creativity of employees. Furthermore, ethical leadership boosted OCB and boosted employee creativity, according to the research. OCB and employee creativity have both been demonstrated to benefit greatly from transformational leadership. Further research revealed that OCB is a mediating factor in the link between leadership styles and creative thinking among employees. Recommendations for Practitioners: Higher education institutions should focus on developing leaders who value transparency and self-awareness in their interactions with followers and who demonstrate an inner moral perspective in addition to balanced information processing to ensure positive outcomes at the individual and organizational levels. Higher education institutions should place a priority on hiring leaders that exhibit ethical and transformational traits to raise awareness of these leadership styles among employees. Recommendation for Researchers: The new study also adds significantly to the body of knowledge by examining the relationship between ethical and transformational leadership and the creativity of the workforce. It aimed to identify the relationship between transformational leadership style and individual creativity in higher education by examining the mediating influence of OCB. Impact on Society: Higher education institutions should devise strategies for developing ethical and transformative leaders who will assist boost OCB and creativity within their workforce. Students and faculty in higher education can benefit from these leadership methods by learning to think in more diverse ways and by developing thought processes that lead to a larger pool of innovative ideas and solutions. As a consequence, employees who show creative behavior may be effectively managed by leaders who utilize ethical and transformational leadership styles and motivate them to show OCB that allow them to solve creative problems creatively. Future Research: A mixed-methods approach should be used in future research, and this should be done in public institutions in developing and developed nations to put the findings to use and generalize them even further. Future research will be able to examine other mediators to learn more about how and why ethical and transformational leadership styles affect PHEI employees’ creativity.

Aim/Purpose. COVID-19 was an unprecedented disruptive event that accelerated the shift to remote work and encouraged widespread adoption of digital tools in organizations. This empirical study was conducted from an organizational-strategic perspective, with the aim of examining how the COVID-19 pandemic outbreak affected employees’ use of organizational information systems (IS) as reflected in frequency. Background. To date, only a limited effort has been made, and a rather narrow perspective has been adopted, regarding the consequences of the adoption of new work environments following COVID-19. It seems that the literature is lacking in information regarding employee use of organizational IS since the outbreak of the pandemic. Specifically, this issue has not yet been examined in relation to employees’ perception about the organization’s digital efforts and technological maturity for remote work. The present study bridges this gap. Methodology. The public sector in Israel, which employs about a third of the Israeli work-force, was chosen as a case study of information-intensive organizations. During the first year of COVID-19, 716 questionnaires were completed by employees and managers belonging to four government ministries operating in Israel. The responses were statistically analyzed using a Chi-Square and Spearman’s Rho tests. Contribution. Given that the global pandemic is an ongoing phenomenon and not a passing episode, the findings provide important theoretical and practical contributions. The period prior to the COVID-19 pandemic and the period of the pandemic are compared with regard to organizational IS use. Specifically, the study sheds new light on the fact that employee perceptions motivated increased IS use during an emergency. The results contribute to the developing body of empirical knowledge in the IS field in the era of digital transformation (DT). Findings. More than half of the respondents who reported that they did not use IS before COVID-19 stated that the pandemic did not change this. We also found a significant positive correlation between the perception of the digital efforts made by organizations to enable connection to the IS for remote work and a change in frequency of IS use. This frequency was also found to have a significant positive correlation with the perception of the organization’s technological maturity to enable effective and continuous remote work. Recommendations for Practitioners. In an era of accelerating DT, this paper provides insights that may support chief information officers and chief digital officers in understanding how to promote the use of IS. The results can be useful for raising awareness of the importance of communicating managerial messages for employees regarding the organizational strategy and the resilience achieved through IS not only in routine, but also in particular in emergency situations. Recommendations for Researchers. Considering that the continual crisis has created challenges in IS research, it is appropriate to continue researching the adaptation and acclimation of organizations to the “new normal”. Impact on Society. The COVID-19 pandemic created a sudden change in employment models, which have become more flexible than ever. The research insights enrich the knowledge about the concrete consequences of this critical change. Future Research. We suggest that researchers investigate this core issue in other sectors and/or other countries, in order to be obtain new and complementary empirical insights on a comparative basis.

Aim/Purpose: This paper aims to empirically quantify the financial distress caused by the COVID-19 pandemic on companies listed on Amman Stock Exchange (ASE). The paper also aims to identify the most important predictors of financial distress pre- and mid-pandemic. Background: The COVID-19 pandemic has had a huge toll, not only on human lives but also on many businesses. This provided the impetus to assess the impact of the pandemic on the financial status of Jordanian companies. Methodology: The initial sample comprised 165 companies, which was cleansed and reduced to 84 companies as per data availability. Financial data pertaining to the 84 companies were collected over a two-year period, 2019 and 2020, to empirically quantify the impact of the pandemic on companies in the dataset. Two approaches were employed. The first approach involved using Multiple Discriminant Analysis (MDA) based on Altman’s (1968) model to obtain the Z-score of each company over the investigation period. The second approach involved developing models using Artificial Neural Networks (ANNs) with 15 standard financial ratios to find out the most important variables in predicting financial distress and create an accurate Financial Distress Prediction (FDP) model. Contribution: This research contributes by providing a better understanding of how financial distress predictors perform during dynamic and risky times. The research confirmed that in spite of the negative impact of COVID-19 on the financial health of companies, the main predictors of financial distress remained relatively steadfast. This indicates that standard financial distress predictors can be regarded as being impervious to extraneous financial and/or health calamities. Findings: Results using MDA indicated that more than 63% of companies in the dataset have a lower Z-score in 2020 when compared to 2019. There was also an 8% increase in distressed companies in 2020, and around 6% of companies came to be no longer healthy. As for the models built using ANNs, results show that the most important variable in predicting financial distress is the Return on Capital. The predictive accuracy for the 2019 and 2020 models measured using the area under the Receiver Operating Characteristic (ROC) graph was 87.5% and 97.6%, respectively. Recommendations for Practitioners: Decision makers and top management are encouraged to focus on the identified highly liquid ratios to make thoughtful decisions and initiate preemptive actions to avoid organizational failure. Recommendation for Researchers: This research can be considered a stepping stone to investigating the impact of COVID-19 on the financial status of companies. Researchers are recommended to replicate the methods used in this research across various business sectors to understand the financial dynamics of companies during uncertain times. Impact on Society: Stakeholders in Jordanian-listed companies should concentrate on the list of most important predictors of financial distress as presented in this study. Future Research: Future research may focus on expanding the scope of this study by including other geographical locations to check for the generalisability of the results. Future research may also include post-COVID-19 data to check for changes in results.

Table of Contents for Volume 19, 2024, of the Interdisciplinary Journal of Information, Knowledge, and Management

Alzheimer's disease (AD), a leading cause of dementia and mortality, presents a growing concern due to its irreversible progression and the rising costs of care. Early detection is crucial for managing AD, which begins with memory deterioration caused by the damage to neurons involved in cognitive functions. Although incurable, treatments can manage its symptoms. This study introduces a hybrid AlexNet+ResNet-50 model for AD diagnosis, utilising a pre-trained convolutional neural network (CNN) through transfer learning to analyse MRI scans. This method classifies MRI images into Alzheimer's disease (AD), moderate cognitive impairment (MCI), and normal control (NC), enhancing model efficiency without starting from scratch. Incorporating transfer learning allows for refining the CNN to categorise these conditions accurately. Our previous work also explored atlas-based segmentation combined with a U-Net model for segmentation, further supporting our findings. The hybrid model demonstrates superior performance, achieving 94.21% accuracy in identifying AD cases, indicating its potential as a highly effective tool for early AD diagnosis and contributing to efforts in managing the disease's impact.

The novel coronavirus pandemic ravaged the world in 2020, making the world fall into an unprecedented period of stagnation. This research used the Sol-Idea internet public opinion analysis platform to collect, and analyses online public opinion data associated with novel coronavirus. This research finds the following situations: 1) COVID-19 online opinion leaders are more likely to post in major discussion boards. However, opinion leaders of replies but use PTT forum as the main discussion channel; 2) According to the analysis of the content and behaviour of the account 'ebola01', it is found that the content of the posts are mostly news praising the ruling party government or mocking the opposing parties, with the sources mostly coming from media considered to be more pro-ruling party. Therefore, it can be inferred that 'ebola01' may be part of cyber army with a particular political spectrum.

In the context of US universities where student evaluations of teaching play an important role in the retention and promotion of faculty, it is important to understand what a student expects in the classroom. This study took the perspective of Perry's cognitive development scheme with the following research question: what is the Perry level of cognitive development of business students? An established survey was used at two different universities. It was found that the median was position 3, and that there was large variation in three dimensions. First is the variation across program levels. Second, there was variation across universities. This becomes an issue when instructors move to a different university and questions the possibility to transfer 'best practices'. Third, variation was found within a specific program level. This means that instructors are faced with students who, from a cognitive perspective, have different demands which are unlikely to be simultaneously met.

Nowadays, we are surrounded by artifacts that are capable of adaptive behavior, such as electric pots, boiler timers, automatic doors, and robots. The literature concerning human beings’ conceptions of “traditional” artifacts is vast, however, little is known about our conceptions of behaving artifacts, nor of the influence of the interaction with such artifacts on cognitive development, especially among children. Since these artifacts are provided with an artificial “mind,” it is of interest to assess whether and how children develop a Theory of Artificial Mind (ToAM) which is distinct from their Theory of Mind (ToM). The study examined a new theoretical scheme named ToAM (Theory of Artificial Mind) by means of qualitative and quantitative methodology among twenty four 5-7 year old children from central Israel. It also examined the effects of interacting with behaving artifacts (constructing versus observing the robot’s behavior) using the “RoboGan” interface on children’s development of ToAM and their ToM and looked for conceptions that evolve among children while interacting with behaving artifacts which are indicative of the acquisition of ToAM. In the quantitative analysis it was found that the interaction with behaving artifacts, whether as observers or constructors and for both age groups, brought into awareness children’s ToM as well as influenced their ability to understand that robots can behave independently and based on external and environmental conditions. In the qualitative analysis it was found that participating in the intervention influenced the children’s ToAM for both constructors and for the younger observer. Engaging in building the robot’s behavior influenced the children’s ability to explain several of the robots’ behaviors, their understanding of the robot’s script-based behavior and rule-based behavior and the children’s metacognitive development. The theoretical and practical importance of the study is discussed.

Can questions sent to Open-Educational-Resource (OER) websites such as Ask-An-Expert serve as indicators for students’ interest in science? This issue was examined using an online questionnaire which included an equal number of questions about the topics “space” and “nutrition” randomly selected from three different sources: a 5th-grade science textbook, the “Ask-An-Expert” website, and questions collected from other students in the same age group. A sample of 113 5th-graders from two elementary schools were asked to rate their interest level in finding out the answer to these questions without knowledge of their source. Significant differences in students’ interest level were found between questions: textbook questions were ranked lowest for both subjects, and questions from the open-resource were ranked high. This finding suggests that questions sent to an open-resource could be used as an indicator of students’ interest in science. In addition, the high correlation of interests expressed by students from the two schools may point to a potential generalization of the findings. This study contributes by highlighting OER as a new and promising indicator of student interest, which may help bring “student voices” into mainstream science teaching to increase student interest in science.

This study seeks to explore what factors influence students’ ICT use and web technology competence. The objectives of this study are the following: (a) To what extent do certain elements of Rogers’ (2003) Diffusion of Innovations Theory (DOI) explain students’ ICT use, (b) To what extent do personality characteristics derived from the Big Five approach explain students’ ICT use, and (c) To what extent does motivation explain students’ ICT use. The research was conducted in Israel during the second semester of the academic year 2013-14, and included two groups of participants: a group of Educational Technology students (ET) and a group of Library and Information Science students (LIS). Findings add another dimension to the importance of Rogers’ DOI theory in the fields of Educational Technology and Library and Information Science. Further, findings confirm that personality characteristics as well as motivation affect ICT use. If instructors would like to enhance students’ ICT use, they should be aware of individual differences between students, and they should present to students the advantages and usefulness of ICT, thus increasing their motivation to use ICT, in the hopes that they will become innovators or early adopters.

In recent years, schools (as well as universities) have added cyber security to their computer science curricula. This topic is still new for most of the current teachers, who would normally have a standard computer science background. Therefore the teachers are trained and then teaching their students what they have just learned. In order to explore differences in both populations’ learning, we compared measures of software quality and security between high-school teachers and students. We collected 109 source files, written in Python by 18 teachers and 31 students, and engineered 32 features, based on common standards for software quality (PEP 8) and security (derived from CERT Secure Coding Standards). We use a multi-view, data-driven approach, by (a) using hierarchical clustering to bottom-up partition the population into groups based on their code-related features and (b) building a decision tree model that predicts whether a student or a teacher wrote a given code (resulting with a LOOCV kappa of 0.751). Overall, our findings suggest that the teachers’ codes have a better quality than the students’ – with a sub-group of the teachers, mostly males, demonstrate better coding than their peers and the students – and that the students’ codes are slightly better secured than the teachers’ codes (although both populations show very low security levels). The findings imply that teachers might benefit from their prior knowledge and experience, but also emphasize the lack of continuous involvement of some of the teachers with code-writing. Therefore, findings shed light on computer science teachers as lifelong learners. Findings also highlight the difference between quality and security in today’s programming paradigms. Implications for these findings are discussed.

Aim/Purpose: The purpose of the current study is to explore positive and negative aspects of teacher-teacher communication via Facebook, as perceived by teachers in secondary education. Background: Teacher-student relationship is key to teachers’ wellness and professional development and may contribute to positive classroom environment. In recent years, as social networking sites (e.g., Facebook) became popular, these connections have extended to such platforms. However, most studies of the use of social networking sites in the school context are pedagogically-driven, and research on the ways teacher-student relationship is facilitated by these platforms is meager. Methodology: We utilized a qualitative approach, analyzing responses to open-ended questions about this topic by middle- and high-school teachers’ all across Israel (N=180). We used both top-down and bottom-up analyses. Contribution: This study contributes to the growing literature about the overall impact of using social networking sites on the educational milieu. Specifically, it contributes by shedding light on teachers’ perspectives of that phenomenon. Insights from this study are important for educators and education policy makers. Findings: Overall, teachers who were connected to their students de facto, as well as teachers who expressed a wish to be connected to their students, acknowledged the advantages of befriending their students on Facebook, in terms of both teacher- and student benefits. Teachers’ overall viewpoint on the negative aspects of Facebook-connections with students is multifaceted. As such, our findings highlight the complexity of using social networking sites by teachers. Recommendations for Practitioners: We recommend that educators who wish to extend the relationship with their student to online platforms do so wisely, taking advantage of the benefits of using these platforms, and being aware of (and cautious about) potential draw-backs. We encourage educators to learn more about the potential uses of social networking sites and instant messaging services, and then to examine whether these uses may fit their educational agenda. We recommend that education policymakers make evidence-based decisions regarding the use of social networking sites by teachers and encourage school communities to discuss these issues together. Recommendation for Researchers: As technology develops rapidly, we recommend that researchers examine the topics raised in the current research with regards to other platforms, in order to better understand the technological aspects that may affect students’ perceptions of the use of social networking sites and instant messaging services to communicate with their students. The issues studied here should also be studied in different cultural contexts. We recommend broadening the research and making results available to policymakers when making decisions regarding social media in educational contexts. Impact on Society: Understanding teachers’ perspectives of their relationship with their students in today’s digital, networked world gives us a better understanding of the changing role of teachers; hence, it may assist in planning teacher training and professional development, with the ultimate goal of realizing a better educational system. Future Research: Future studies should focus on other social networking sites and instant messaging services, as well as on other countries and cultures.

Table of Contents of the Interdisciplinary Journal of E-Skills and Lifelong Learning