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The purpose of this paper is to describe a proposal for a data-driven investigation aimed at determining whether students’ learning behavior can be extracted and visualized from action logs recorded by Moodle. The paper also tried to show whether there is a correlation between the activity level of students in online environments and their academic performance with respect to final grade.

The analysis was carried out using log data obtained from various courses dispensed in a university using a Moodle platform. The study also collected demographic profiles of students and compared them with their activity level in order to analyze how these attributes affect students’ level of activity in the online environment.

This work has shown that data mining algorithm like vector space model can be used to aggregate the action logs of students and quantify it into a single numeric value that can be used to generate visualizations of students’ level of activity. The current investigation indicates that there is a lot of variability in terms of the correlation between these two variables.

The value presented in the study can help instructors monitor course progression and enable them to rapidly identify which students are not performing well and adjust their pedagogical strategies accordingly.

A plan to continue the work by developing a complete dashboard style interface that instructors can use is already underway. More data need to be collected and more advanced processing tools are necessary in order to obtain a better perspective on this issue.

This paper aims to demonstrate that state shareholders are confronted with contradictory logics leading to institutional contradictions that activist shareholders can exploit. The competing logics of the state as shareholder and their impact on corporate governance and shareholder activism offer fertile grounds for research advances in Coordinated Market Economies (CMEs).

Through an extensive literature review of state ownership, institutional contradictions and shareholder activism, this paper analyzes two case studies involving the French State as shareholder.

In the French context, these two cases illustrate how institutional contradictions result in opportunities for shareholder activism. By focusing on the institutional contradictions of the state shareholder, this investigation suggests a need for experimental research to observe how shareholder activists adapt to each institutional change in CMEs. This experimentation can help policymakers to avoid creating additional conditions that shareholder activists can exploit.

This focuses only on France and its state shareholdings. To generalize results, studies of other CMEs and state shareholders are needed.

Policymakers should consider all legislative proposals for their potential to deviate from corporate governance practice by experimenting with them in a laboratory setting. Shareholder activists can compare state shareholders’ actions against the state’s legislation to emphasize institutional contradictions that counter minority shareholders’ rights.

This research is the first to analyze how the state as shareholder can exploit its competing logics to resist against shareholder activism and support management or to become itself a shareholder activist.

This paper focuses on patterns of film consumption within cultural consumption more broadly to assess trends in consumerism such as eclectic consumption, individualised consumption and omnivorous/univorous consumption and whether economic background and status feature in shaping cultural consumption. We focus on film because it is widely consumed, online and offline, and has many genres that vary in terms of perceived artistic and entertainment value. In broad terms, film is differentiated between mainstream commercially driven film such as Hollywood blockbusters, middlebrow “feel good” movies and independent arthouse and foreign language film. Our empirical statistical analysis shows that film consumers watch a wide range of genres. However, films deemed to hold artistic value such as arthouse and foreign language feature as part of broad and wide-ranging pattern of consumption of film that attracts its own dedicated consumers. Though we found that social and economic factors remain predictors of cultural consumption the overall picture is more complex than a simple direct correspondence and perceptions of other cultural forms also play a role. Those likely to consume arthouse and foreign language film consume other film genres and other cultural forms genres and those who “prefer” arthouse and foreign language film have slightly more constrained socio-economic characteristics. Overall, we find that economic and cultural factors such income, education, and wider consumption of culture are significant in patterns of film consumption.

Perception has been identified as the main cause underlying most autonomous vehicle related accidents. As the key technology in perception, deep learning (DL) based computer vision models are generally considered to be black boxes due to poor interpretability. These have exacerbated user distrust and further forestalled their widespread deployment in practical usage. This paper aims to develop explainable DL models for autonomous driving by jointly predicting potential driving actions with corresponding explanations. The explainable DL models can not only boost user trust in autonomy but also serve as a diagnostic approach to identify any model deficiencies or limitations during the system development phase.

This paper proposes an explainable end-to-end autonomous driving system based on “Transformer,” a state-of-the-art self-attention (SA) based model. The model maps visual features from images collected by onboard cameras to guide potential driving actions with corresponding explanations, and aims to achieve soft attention over the image’s global features.

The results demonstrate the efficacy of the proposed model as it exhibits superior performance (in terms of correct prediction of actions and explanations) compared to the benchmark model by a significant margin with much lower computational cost on a public data set (BDD-OIA). From the ablation studies, the proposed SA module also outperforms other attention mechanisms in feature fusion and can generate meaningful representations for downstream prediction.

In the contexts of situational awareness and driver assistance, the proposed model can perform as a driving alarm system for both human-driven vehicles and autonomous vehicles because it is capable of quickly understanding/characterizing the environment and identifying any infeasible driving actions. In addition, the extra explanation head of the proposed model provides an extra channel for sanity checks to guarantee that the model learns the ideal causal relationships. This provision is critical in the development of autonomous systems.

The first part presents a review of concepts relating to reflection, drawing on the literature in this area. This literature review relates to the following aspects of reflection: the definition of reflection, the process of reflection, strategies in reflection, content of reflection, barriers to reflection, and advantages of reflection.

The second part of this paper presents an investigation into the perceptions of a small sample of English language educators and supervisors, through personal interviews with 9 teachers and 3 supervisors from one higher education institution and other educational institutions in the United Arab Emirates. The findings of the investigation are analyzed with respect to the dimensions that appear in the literature review. These findings show that the teachers do have some knowledge of reflection. They reveal that the teachers: attitudes towards reflection and its applicability in the teaching and learning process is largely positive, mixed with some degree of skepticism. Teachers agree that reflection is useful, but many seem uncertain about how it can be applied in their situation. In some cases the interviewees seemed to be more concerned about the technicalities of their job, making collaborative reflection appear less of a priority.

This paper aims to examine the cycle of labour protests in Sweden, comparing the contentious actions of trade unions in public and private sectors over 40 years. Prior studies have focused on industrial conflicts or labour protests, but a long-term perspective on the broad protest repertoire across sectors is lacking. The goal is to test the argument of diversification of action repertoire and differences between the public and private sectors.

The authors apply the grievance and political opportunity theories of social movement research for explaining the cycles of labour protests and differences between sectors in Sweden over 40 years (1980–2020). The unique protest event data are combined with the official strike statistics. The research period includes the globalisation of the economy and two economic crises.

Although unions in both sectors have decreased protest mobilisation over time, private sector unions have resigned the most, whereas public sector unions continue to mobilise a diverse set of protest actions. Swedish unions have not replaced strikes with other protest repertoires. The open opportunities have allowed them to use various protests as part of “routine” operations.

Protest event data are derived from newspapers, leading to an over-representation of large events in the urban areas. Future studies should combine data from newspapers with data about online protests.

By thoroughly examining all protest events mobilised by all trade unions in different sectors over 40 years (1980–2020), the paper presents a comprehensive analysis of the cycles of labour protest. The findings should interest industrial relations and social movement scholars.