This paper puts forward a verification method for compound purposes and compound reasons to be used during purpose limitation.

When it is absolutely necessary to collect privacy related information, it is essential that privacy enhancing technologies (PETs) protect access to data - in general accomplished by using the concept of purposes bound to data. Compound purposes and reasons are an enhancement of purposes used during purpose limitation and binding and are more expressive than purposes in their general form. Data users specify their access needs by making use of compound reasons which are defined in terms of (compound) purposes. Purposes are organised in a lattice with purposes near the greatest lower bound (GLB) considered weak (less specific) and purposes near the least upper bound (LUB) considered strong (most specific).

Access is granted based on the verification of the statement of intent (from the data user) against the compound purpose bound to the data; however, because purposes are in a lattice, the data user is not limited to a statement of intent that matches the purposes bound to the data exactly - the statement can be a true reflection of their intent with the data. Hence, the verification of compound reasons against compound purposes cannot be accomplished by current published verification algorithms.

Before presenting the verification method, compound purposes and reasons, as well as the structures used to represent them, and the operators that are used to define compounds is presented. Finally, some thoughts on implementation are provided.

L'actualité aidant, une personne sur twitter a exhumé un vieux billet que j'avais écrit en Mai 2011. A l'époque, je parlais du Parti Socialiste... sans fausse modestie, j'avais vu plutôt juste... Aujourd'hui, on peut déjà parler d'un autre "parti" mais...

Depuis quelques années, la théorie du grand remplacement, popularisée par Michel Houellbecq dans Soumissions ou par un Eric Zemmour, a fait son chemin dans les arcanes les moins visibles du Net. Pourtant, le danger n’est pas là, loin s’en faut, il est...

1. "Gladiator II" : comment Hollywood se jette dans l'arène politique avec ses péplums  franceinfo
2. « Gladiator », le film qui ressuscite les morts et détruit le cinéma  Le Monde
3. "Gladiator II" : "Ridley Scott respecte surtout les codes bien établis du gladiateur hollywoodien", estime un spécialiste  franceinfo
4. « Gladiator II » : bis repetita, triste cirque  Le Point
5. Gladiator 2, Une part manquante, Le royaume… les films à voir ou à éviter cette semaine  La Provence

1. What is walking pneumonia? As cases rise in Canada, the symptoms to look out for  The Globe and Mail
2. Walking pneumonia on the rise in Kingston, but treatable  The Kingston Whig-Standard
3. What parents need to know about walking pneumonia in kids  FingerLakes1.com
4. Pediatric pneumonia is surging in Central Ohio  MSN
5. Walking Pneumonia is spiking right now. How do you know you have it?  CBS 6 News Richmond WTVR

1. Ottawa businesses brace for possible Canada Post strike before the holiday season  CTV News Ottawa
2. Tougher work conditions for postal workers at the heart of labour dispute, union says  The Globe and Mail
3. Ottawa businesses worry about potential postal disruption  CBC.ca
4. Calgary workers 'ready to go' if Canada Post, CUPW unable to reach agreement by Friday: union president  Calgary Herald
5. ‘Feeling the pinch’: Potential postal strike may be first of many, Manitoba prof says  Global News Toronto

Le 20 avril 2018, un appel au boycott a été lancé sur les réseaux sociaux marocains contre trois entreprises leaders dans leurs secteurs d’activités. L’eau minérale de Sidi Ali, le lait de Centrale Danone et les stations de services Afriquia (pétrole) ont été victimes d’une guerre d’information, justifiée selon les internautes par des prix de vente élevés. Les appels au boycott ont été relayés par les internautes Marocains via des groupes et des pages ...

Elon Musk a tenté de montrer lundi au tribunal que ses fameux tweets de 2018, sur sa volonté de sortir Tesla de la Bourse, n'avaient rien de trompeurs ou de frauduleux, contrairement aux accusations d'investisseurs qui disent avoir perdu des millions de dollars à cause du milliardaire.

Le patron de Tesla -- et de Twitter, depuis fin octobre -- a assuré qu'il n'avait "jamais" cherché à tromper les investisseurs, et que l'accusation de fraude était "scandaleuse".

Il avait créé la stupeur le 7 août 2018 en affirmant qu'il voulait retirer son groupe automobile de la Bourse au prix de 420 dollars par action, puis en assurant que le financement était "sécurisé".

"Je ne disais pas que c'était fait, je disais simplement que je l'envisageais, que j'y pensais. Et qu'à mon avis le financement était sécurisé", a déclaré Elon Musk à la barre, dans le tribunal de San Francisco où a lieu le procès.

La semaine dernière, le principal avocat des plaignants, Nicholas Porritt, avait accusé le dirigeant d'avoir "menti" et d'être responsable des pertes des investisseurs.

Le titre avait bondi dans la foulée des tweets très inhabituels (et le Nasdaq avait temporairement suspendu le cours de l'action Tesla), avant de décliner les jours suivants. Des articles de presse avaient fini par révéler que le patron n'avait pas vraiment les fonds.

Tesla était restée cotée en Bourse.

A travers ses questions, Nicholas Porritt a cherché à montrer qu'Elon Musk n'avait pas réalisé les consultations appropriées, et ne disposait pas ni des éléments nécessaires, ni de l'autorité pour faire une annonce aussi fracassante, surtout sur Twitter, et surtout pendant que les marchés étaient ouverts.

- "M. Tweet" -

L'avocat a mis en avant des échanges acerbes le 12 août 2018 entre le milliardaire et Yasir Al-Rumayyan, le directeur du fonds souverain saoudien, qui s'était engagé "catégoriquement" et "sans hésitation" à financer l'opération, selon Elon Musk.

"Le financement n'était pas vraiment sécurisé, n'est-ce pas?", a demandé M Porritt.

Yasir Al-Rumayyan a fait du "rétropédalage", a rétorqué le patron de Tesla.

Il a assuré qu'il avait de toute façon la possibilité de vendre ses actions de son autre fleuron, SpaceX, "l'entreprise non cotée la plus valorisée des Etats-Unis".

"Cela m'aurait brisé le cœur (de les vendre), mais je l'aurais fait si besoin", a-t-il déclaré, évoquant comment il avait dû se séparer d'actions de Tesla pour racheter Twitter l'année dernière.

Costume sombre, chemise blanche et cravate, il est apparu hésitant, ne se souvenant pas de nombreux emails et détails, et répondant souvent à côté des questions pour répéter à l'envie les messages qu'il voulait faire passer au jury.

Au point de faire perdre patience à l'avocat des investisseurs. "Nous avons passé toute une journée ensemble à Austin, vous vous en souvenez M. Tweet?!", a lancé Nicholas Porritt, avant de corriger pour "M. Musk".

- "Karma" -

L'accusation est aussi revenue sur le prix proposé par Elon Musk, 420 dollars par action. Aux Etats-Unis, les chiffres 4 et 20 accolés sont associés à la consommation de cannabis. Quand le milliardaire a proposé de racheter Twitter au printemps dernier, il a choisi un prix de 54,20 dollars par action.

"Avez-vous arrondi à 420 en guise de blague à l'attention de votre petite amie?", a demandé Nicholas Porritt.

"Ce n'était pas une blague, cela représentait une prime de 20% au-dessus du prix de l'action", a répondu Elon Musk, reconnaissant cependant qu'il y a "un certain karma autour de 420".

"Pas sûr que ce soit un bon ou un mauvais karma à ce stade", a-t-il encore plaisanté.

Son avocat Alex Spiro l'a ensuite aidé à dresser le portrait d'un immigré parti de rien, venu aux Etats-Unis - "là où les grandes choses sont possibles" - après une enfance "malheureuse" en Afrique du Sud, selon les mots du milliardaire.

"On m'a traité de fou à de nombreuses reprises", a déclaré Elon Musk après avoir énuméré les entreprises qu'il a cofondées.

Mais "à ce stade je crois que j'ai levé plus d'argent que quiconque dans l'histoire", s'est-il vanté, attribuant sa réussite à son "honnêteté" à l'égard des investisseurs.

Le procès doit durer trois semaines. Dans une précédente décision liée à cette affaire, un juge avait estimé que le fameux tweet de 2018 pouvait être considéré comme "faux et trompeur".

Le gendarme boursier américain, la SEC, avait de son côté obligé Elon Musk à céder la présidence du conseil d'administration, à payer une amende et à faire pré-approuver par un juriste ses tweets directement liés à l'activité de Tesla.

Vous n'avez pas eu le temps de lire Le Canard enchaￜnￜ, Mediapart, Le Monde, Arrￜt sur images et tous les autres titres de presse ? On s'en charge pour vous.

La crise ? Quelle crise ? Alors que le gouvernement prￜpare l'opinion ￜ une longue pￜriode d'inflation et de hausse des prix de l'ￜnergie en raison de la guerre en Ukraine, tout ne va pas si mal sur le plan...

Despite the considerable growth potential predicted for mobile games, little research explored what motivates users to be sticky and make purchases in the mobile game context. Drawing on uses and gratifications theory (UGT), this study evaluates the influencing effects of players' characteristics (i.e., individual gratification and individual situation) and the mobile game structure (i.e., presence and governance) on players' mobile game behaviour (i.e., stickiness and purchase intention). Specifically, the model was extended with factors of the individual situation and governance. After surveying 439 samples, the research model was examined using the Partial least squares structural equation modelling (PLS-SEM) approach. The results indicate that stickiness is a crucial antecedent for users' in-game purchase intention. The individual situation plays an essential role in influencing user gratification, and individual gratification is the most vital criterion affecting stickiness. Finally, except for incentives, presence, and integration positively affect stickiness. This study provides further insights into both mobile game design and governance strategies.

We propose that technological, service-dominant and design logics must interplay for an IT artefact to succeed. Based on data from a project aiming at a B2B platform for manufacturing small and medium enterprises (SMEs) in Europe, we explore these three logics in an agile software design context. By using an inductive approach, we theorise about what is needed for the alignment of the three logics. We contribute with a novel theoretical lens, the Framework for Adaptive Space. We offer insights into the importance of continuously reflecting on all three logics during the agile software design process to ensure mutual understanding among the agile team and the B2B platform end-users involved.

Emergency disaster management presents substantial risks and obstacles to shield tunnel building projects, particularly in the event of water leakage accidents. Contemporary water leak detection is critical for guaranteeing safety by reducing the likelihood of disasters and the severity of any resulting damages. However, it can be difficult. Deep learning models can analyse images taken inside the tunnel to look for signs of water damage. This study introduces a unique strategy that employs deep learning techniques, generative adversarial networks (GAN) with long short-term memory (LSTM) for water leakage detection i shield tunnel construction (WLD-STC) to conduct classification and prediction tasks on the massive image dataset. The results demonstrate that for identifying and analysing water leakage episodes during shield tunnel construction, the WLD-STC strategy using LSTM-based GAN networks outperformed other methods, particularly on huge data.

In this paper we discuss the use of automated assessment in a variety of computer science courses that have been taught at Israel Academic College by the authors. The course assignments were assessed entirely automatically using Checkpoint, a web-based automated assessment framework. The assignments all used free-text questions (where the students type in their own answers). Students were allowed to correct errors based on feedback provided by the system and resubmit their answers. A total of 141 students were surveyed to assess their opinions of this approach, and we analysed their responses. Analysis of the questionnaire showed a low correlation between questions, indicating the statistical independence of the individual questions. As a whole, student feedback on using Checkpoint was very positive, emphasizing the benefits of multiple attempts, impartial marking, and a quick turnaround time for submissions. Many students said that Checkpoint gave them confidence in learning and motivation to practise. Students also said that the detailed feedback that Checkpoint generated when their programs failed helped them understand their mistakes and how to correct them.

An online Moodle Workshop was evaluated for peer assessment effectiveness. A quasi-experiment was designed using a Seminar in Professionalism course taught in face-to-face mode to undergraduate students across two campuses. The first goal was to determine if Moodle Workshop awarded a fair peer grader grade. The second objective was to estimate if students were consistent and reliable in performing their peer assessments. Statistical techniques were used to answer the research hypotheses. Although Workshop Moodle did not have a built-in measure for peer assessment validity, t-tests and reliability estimates were calculated to demonstrate that the grades were consistent with what faculty expected. Implications were asserted to improve teaching and recommendations were provided to enhance Moodle.

Since the advent of the iPhone and rise of mobile technologies, educational apps represent one of the fastest growing markets, and both the mobile technology and educational app markets are predicted to continue experiencing growth into the foreseeable future. The irony, however, is that even with a booming market for educational apps, very little research regarding the quality of them has been conducted. Though some instruments have been developed to evaluate apps geared towards student learning, no such instrument has been created for teacher resource apps, which are designed to assist teachers in completing common tasks (e.g., taking attendance, communicating with parents, monitoring student learning and behavior, etc.). Moreover, when teachers visit the App Store or Google Play to learn about apps, the only ratings provided to them are generic, five-point evaluations, which do not provide qualifiers that explain why an app earned three, two, or five points. To address that gap, previously conducted research related to designing instructional technologies coupled with best practices for supporting teachers were first identified. That information was then used to construct a comprehensive rubric for assessing teacher re-source apps. In this article, a discussion that explains the need for such a rubric is offered before describing the process used to create it. The article then presents the rubric and discusses its different components and potential limitations and concludes with suggestions for future research based on the rubric.

Aim/Purpose: This paper provides a review of previously published work related to active learning in information systems (IS) courses. Background: There are a rising number of strategies in higher education that offer promise in regards to getting students’ attention and helping them learn, such as flipped classrooms and offering courses online. These learning strategies are part of the pedagogical technique known as active learning. Active learning is a strategy that became popular in the early 1990s and has proven itself as a valid tool for helping students to be engaged with learning. Methodology: This work follows a systematic method for identifying and coding previous research based on an aspect of interest. The authors identified and assessed research through a search of ABI/Inform scholarly journal abstracts and keywords, as well as additional research databases, using the search terms “active learning” and “information systems” from 2000 through June 2016. Contribution: This synthesis of active learning exercises provides guidance for information technology faculty looking to implement active learning strategies in their classroom by demonstrating how IS faculty might begin to introduce more active learning techniques in their teaching as well as by presenting a sample teaching agenda for a class that uses a mix of active and passive learning techniques to engage student learning. Findings: Twenty successful types of active learning exercises in IS courses are presented. Recommendations for Practitioners : This paper offers a “how to” resource of successful active learning strategies for IS faculty interested in implementing active learning in the classroom. Recommendation for Researchers: This work provides an example of a systematic literature review as a means to assess successful implementations of active learning in IS. Impact on Society: An updated definition of active learning is presented as well as a meaningful list of exercises that encourage active learning both inside and outside of the IS classroom. Future Research: In relation to future research, this study highlights a number of opportunities for IS faculty in regards to new active learning activities or trends to study further.

Aim/Purpose: The aims of this study were to investigate the feasibility of automatic assessment of programming tasks and to compare manual assessment with automatic assessment in terms of the effect of the different assessment methods on the marks of the students. Background: Manual assessment of programs written by students can be tedious. The assistance of automatic assessment methods might possibly assist in reducing the assessment burden, but there may be drawbacks diminishing the benefits of applying automatic assessment. The paper reports on the experience of a lecturer trying to introduce automated grading. Students’ solutions to a practical Java programming test were assessed both manually and automatically and the lecturer tied the experience to the unified theory of acceptance and use of technology (UTAUT). Methodology: The participants were 226 first-year students registered for a Java programming course. Of the tests the participants submitted, 214 were assessed both manually and automatically. Various statistical methods were used to compare the manual assessment of student’s solutions with the automatic assessment of the same solutions. A detailed investigation of reasons for differences was also carried out. A further data collection method was the lecturer’s reflection on the feasibility of automatic assessment of programming tasks based on the UTAUT. Contribution: This study enhances the knowledge regarding benefits and drawbacks of automatic assessment of students’ programming tasks. The research contributes to the UTAUT by applying it in a context where it has hardly been used. Furthermore, the study is a confirmation of previous work stating that automatic assessment may be less reliable for students with lower marks, but more trustworthy for the high achieving students. Findings: An automatic assessment tool verifying functional correctness might be feasible for assessment of programs written during practical lab sessions but could be less useful for practical tests and exams where functional, conceptual and structural correctness should be evaluated. In addition, the researchers found that automatic assessment seemed to be more suitable for assessing high achieving students. Recommendations for Practitioners: This paper makes it clear that lecturers should know what assessment goals they want to achieve. The appropriate method of assessment should be chosen wisely. In addition, practitioners should be aware of the drawbacks of automatic assessment before choosing it. Recommendation for Researchers: This work serves as an example of how researchers can apply the UTAUT theory when conducting qualitative research in different contexts. Impact on Society: The study would be of interest to lecturers considering automated assessment. The two assessments used in the study are typical of the way grading takes place in practice and may help lecturers understand what could happen if they switch from manual to automatic assessment. Future Research: Investigate the feasibility of automatic assessment of students’ programming tasks in a practical lab environment while accounting for structural, functional and conceptual assessment goals.

Aim/Purpose: The aim of this article is to develop a tool to detect plagiarism in real time amongst students being evaluated for learning in a computer-based assessment setting. Background: Cheating or copying all or part of source code of a program is a serious concern to academic institutions. Many academic institutions apply a combination of policy driven and plagiarism detection approaches. These mechanisms are either proactive or reactive and focus on identifying, catching, and punishing those found to have cheated or plagiarized. To be more effective against plagiarism, mechanisms that detect cheating or colluding in real-time are desirable. Methodology: In the development of a tool for real-time plagiarism prevention, literature review and prototyping was used. The prototype was implemented in Delphi programming language using Indy components. Contribution: A real-time plagiarism detection tool suitable for use in a computer-based assessment setting is developed. This tool can be used to complement other existing mechanisms. Findings: The developed tool was tested in an environment with 55 personal computers and found to be effective in detecting unauthorized access to internet, intranet, and USB ports on the personal computers. Recommendations for Practitioners: The developed tool is suitable for use in any environment where computer-based evaluation may be conducted. Recommendation for Researchers: This work provides a set of criteria for developing a real-time plagiarism prevention tool for use in a computer-based assessment. Impact on Society: The developed tool prevents academic dishonesty during an assessment process, consequently, inculcating confidence in the assessment processes and respectability of the education system in the society. Future Research: As future work, we propose a comparison between our tool and other such tools for its performance and its features. In addition, we want to extend our work to include testing for scalability of the tool to larger settings.

Aim/Purpose: This paper presents a data mining approach for analyzing responses to advanced declarative programming questions. The goal of this research is to find a model that can explain the results obtained by students when they perform exams with Constructed Response questions and with equivalent Multiple-Choice Questions. Background: The assessment of acquired knowledge is a fundamental role in the teaching-learning process. It helps to identify the factors that can contribute to the teacher in the developing of pedagogical methods and evaluation tools and it also contributes to the self-regulation process of learning. However, better format of questions to assess declarative programming knowledge is still a subject of ongoing debate. While some research advocates the use of constructed responses, others emphasize the potential of multiple-choice questions. Methodology: A sensitivity analysis was applied to extract useful knowledge from the relevance of the characteristics (i.e., the input variables) used for the data mining process to compute the score. Contribution: Such knowledge helps the teachers to decide which format they must consider with respect to the objectives and expected students results. Findings: The results shown a set of factors that influence the discrepancy between answers in both formats. Recommendations for Practitioners: Teachers can make an informed decision about whether to choose multiple-choice questions or constructed-response taking into account the results of this study. Recommendation for Researchers: In this study a block of exams with CR questions is verified to complement the area of learning, returning greater performance in the evaluation of students and improving the teaching-learning process. Impact on Society: The results of this research confirm the findings of several other researchers that the use of ICT and the application of MCQ is an added value in the evaluation process. In most cases the student is more likely to succeed with MCQ, however if the teacher prefers to evaluate with CR other research approaches are needed. Future Research: Future research must include other question formats.

Aim/Purpose: The purpose of this study is to develop an efficient methodology that can assist the evaluators in assessing a variable number of individuals that are working in groups and guarantee that the assessment is dependent on the group members’ performance and contribution to the work developed. Background: Collaborative work has been gaining more popularity in academic settings. However, group assessment needs to be performed according to each individual’s performance. The problem rests on the need to distinguish each member of the group in order to provide fair and unbiased assessments. Methodology: Design Science Research methodology supported the design of a framework able to provide the evaluator with the means to distinguish individuals in a workgroup and deliver fair results. Hevner’s DSR guidelines were fulfilled in order to describe WebAVALIA. To evaluate the framework, a quantitative study was performed and the first results are presented. Contribution: This paper provides a methodological solution regarding a fair evaluation of collaborative work through a tool that allows its users to perform their own assessment and peer assessment. These are made accordingly to the user’s perspectives on the performance of each group member throughout the work development. Findings: The first analysis of the results indicates that the developed method provides fairness in the assessment of group members, delivering a distinction amongst individuals. Therefore, each group member obtains a mark that corresponds to their specific contribution to the workgroup. Recommendations for Practitioners: For those who intend to apply this workgroup assessment method, it is relevant to raise student awareness about the methodology that is going to be used. That is, all the functionalities and steps in WebAVALIA have to be thoroughly explained before beginning of the project. Then, the evaluators have to decide about the students’ intermediate voting, namely if the evaluator chooses or not to publish student results throughout the project’s development. If there is the decision to display these intermediate results, the evaluator must try to encourage collaboration among workgroup members, instead of competition. Recommendation for Researchers: This study explores the design and development of an e-assessment tool – WebAVALIA. In order to assess its feasibility, its use in other institutions or contexts is recommended. The gathering of user opinions is suggested as well. It would then be interesting to compare the findings of this study with the results from other experimentations Impact on Society: Sometimes, people develop a rejection of collaborative work because they feel exploited due to the biased evaluation results. However, the group members assessment distinction, according to each one’s performance, may give each individual a sense of fairness and reward, leading to an openness/willingness towards collaborative work. Future Research: As future work, there are plans to implement the method in other group assessment contexts – such as sports and business environments, other higher education institutions, technical training students – in other cultures and countries. From this myriad of contexts, satisfaction results would be compared. Other future plans are to further explore the mathematical formulations and the respective WebAVALIA supporting algorithms.

Aim/Purpose: The aim of this study is to understand student’s opinions and perceptions about e-assessment when the assessment process was changed from the traditional computer assisted method to a multiple-choice Moodle based method. Background: In order to implement continuous assessment to a large number of students, several shifts are necessary, which implies as many different tests as the number of shifts required. Consequently, it is difficult to ensure homogeneity through the different tests and a huge amount of grading time is needed. These problems related to the traditional assessment based on computer assisted tests, lead to a re-design of the assessment resulting in the use of multiple-choice Moodle tests. Methodology: A longitudinal, concurrent, mixed method study was implemented over a five-year period. A survey was developed and carried out by 815 undergraduate students who experienced the electronic multiple-choice questions (eMCQ) assessment in the courses of the IS department. Qualitative analyses included open-ended survey responses and interviews with repeating students in the first year. Contribution: This study provides a reflection tool on how to incorporate frequent moments of assessment in courses with a high number of students without overloading teachers with a huge workload. The research analysed the efficiency of assessing non-theoretical topics using eMCQ, while ensuring the homogeneity of assessment tests, which needs to be complemented with other assessment methods in order to assure that students develop and acquire the expected skills and competencies. Findings: The students involved in the study appreciate the online multiple-choice quiz assessment method and perceive it as fair but have a contradictory opinion regarding the preference of the assessment method, throughout the years. These changes in perception may be related to the improvement of the question bank and categorisation of questions according to difficulty level, which lead to the nullification of the ‘luck factor’. Other major findings are that although the online multiple-choice quizzes are used with success in the assessment of theoretical topics, the same is not in evidence regarding practical topics. Therefore, this assessment needs to be complemented with other methods in order to achieve the expected learning outcomes. Recommendations for Practitioners: In order to be able to evaluate the same expected learning outcomes in practical topics, particularly in technology and information systems subjects, the evaluator should complement the online multiple-choice quiz assessment with other approaches, such as a PBL method, homework assignments, and/or other tasks performed during the semester. Recommendation for Researchers: This study explores e-assessment with online multiple-choice quizzes in higher education. It provides a survey that can be applied in other institutions that are also using online multiple-choice quizzes to assess non-theorical topics. In order to better understand the students’ opinions on the development of skills and competencies with online multiple-choice quizzes and on the other hand with classical computer assisted assessment, it would be necessary to add questions concerning these aspects. It would then be interesting to compare the findings of this study with the results from other institutions. Impact on Society: The increasing number of students in higher education has led to a raised use of e-assessment activities, since it can provide a fast and efficient manner to assess a high number of students. Therefore, this research provides meaningful insight of the stakeholders’ perceptions of online multiple-choice quizzes about practical topics. Future Research: An interesting study, in the future, would be to obtain the opinions of a particular set of students on two tests, one of the tests using online multiple-choice quizzes and the other through a classical computer assisted assessment method. A natural extension of the present study is a comparative analysis regarding the grades obtained by students who performed one or another type of assessment (online multiple-choice quizzes vs. classical computer assisted assessment).

Aim/Purpose: The purpose of this paper is to develop and evaluate a debiasing-based approach to assessing the learning materials in problem-based learning (PBL) environments. Background: Research in cognitive debiasing suggests nine debiasing strategies improve decision-making. Given the large number of decisions made in semester-long, problem-based learning projects, multiple tools and techniques help students make decisions. However, instructors may struggle to identify the specific tools or techniques that could be modified to best improve students’ decision-making in the project. Furthermore, a structured approach for identifying these modifications is lacking. Such an approach would match the debiasing strategies with the tools and techniques. Methodology: This debiasing framework for the PBL environment is developed through a study of debiasing literature and applied within an e-commerce course using the Model for Improvement, continuous improvement process, as an illustrative case to show its potential. In addition, a survey of the students, archival information, and participant observation provided feedback on the debiasing framework and its ability to assess the tools and techniques within the PBL environment. Contribution: This paper demonstrates how debiasing theory can be used within a continuous improvement process for PBL courses. By focusing on a cognitive debiasing-based approach, this debiasing framework helps instructors 1) identify what tools and techniques to change in an PBL environment, and 2) assess which tools and techniques failed to debias the students adequately, providing potential changes for future cycles. Findings: Using the debiasing framework in an e-commerce course with significant PBL elements provides evidence that this framework can be used within IS courses and more broadly. In this particular case, the change identified in a prior cycle proved effective and additional issues were identified for improvement. Recommendations for Practitioners: With the growing usage of semester-long PBL projects in business schools, instructors need to ensure that their design of the projects incorporates techniques that improve student learning and decision making. This approach provides a means for assessing the quality of that design. Recommendation for Researchers: This study uses debiasing theory to improve course techniques. Researchers interested in assessment, course improvement, and program improvement should incorporate debiasing theory within PBL environments or other types of decision-making scenarios. Impact on Society: Increased awareness of cognitive biases can help instructors, students, and professionals make better decisions and recommendations. By developing a framework for evaluating cognitive debiasing strategies, we help instructors improve projects that prepare students for complex and multifaceted real-world projects. Future Research: The approach could be applied to multiple contexts, within other courses, and more widely within information systems to extend this research. The framework might also be refined to make it more concise, integrated with assessment, or usable in more contexts.

Aim/Purpose: During the education of future engineers and experts in the field of computer science and information communication technology, the achievement of learning outcomes related to different levels of cognitive ability and knowledge dimensions can be a challenge. Background: Teachers need to design an appropriate set of activities for students and combine theory-based knowledge acquisition with practical training in technical skills. Including various activities for formative assessment during the course can positively affect students’ motivation for learning and ensure appropriate and timely feedback that will guide students in further learning. Methodology: The aim of the research presented in this paper is to propose an approach for course delivery in the field of software engineering and to determine whether the use of the approach increases student’s academic achievement. Using the proposed approach, the course Process Modeling for undergraduate students was redesigned and experimental study was conducted. Course results of the students (N=82) who took the new version of the course (experimental group) were compared to the results of the students from the control group (N=66). Contribution: An approach for a blended learning course in the field of software engineering was developed. This approach is based on the formative assessment activities that promote collaboration and the use of digital tools. Newly designed activities are used to encourage a greater level of acquired theoretical content and enhance the acquisition of subject-specific skills needed for practical tasks. Findings: The results showed that students who participated in the formative assessment activities achieved significantly better results. They had significantly higher scores in the main components of assessment compared to the students from the control group. In addition, students from the experimental group expressed positive views about the effectiveness of the used approach. Recommendations for Practitioners: The proposed approach has potential to increase students’ motivation and academic achievements so practitioners should consider to apply it in their own context. Recommendation for Researchers: Researchers are encouraged to conduct additional studies to explore the effectiveness of the approach with different courses and participants as well as to provide further insights regarding its applicability and acceptance by students. Impact on Society: The paper provides an approach and an example of good practice that may be beneficial for the university teachers in the field of computer science, information-communication technology, and engineering. Future Research: In the future, face-to-face activities will be adapted for performance in an online environment. Future work will also include a research on the possibilities of personalization of activities in accordance with the students’ characteristics.

Aim/Purpose: This paper focuses on designing and implementing the rubric for objective JAVA programming assessments. An unsupervised learning approach was used to group learners based on their performance in the results obtained from the rubric, reflecting their learning ability. Background: Students' learning outcomes have been evaluated subjectively using a rubric for years. Subjective assessments are simple to construct yet inconsistent and biased to evaluate. Objective assessments are stable, reliable, and easy to conduct. However, they usually lack rubrics. Methodology: In this study, a Top-Down assessment approach is followed, i.e., a rubric focused on the learning outcome of the subject is designed, and the proficiency of learners is judged by their performance in conducting the task given. A JAVA rubric is proposed based on the learning outcomes like syntactical, logical, conceptual, and advanced JAVA skills. A JAVA objective quiz (with multiple correct options) is prepared based on the rubric criteria, comprising five questions per criterion. The examination was conducted for 209 students (100 from the MCA course and 109 from B.Tech. course). The suggested rubric was used to compute the results. K-means clustering was applied to the results to classify the students according to their learning preferences and abilities. Contribution: This work contributes to the field of rubric designing by creating an objective programming assessment and analyzing the learners’ performance using machine learning techniques. It also facilitates a reliable feedback approach offering various possibilities in student learning analytics. Findings: The designed rubric, partial scoring, and cluster analysis of the results help us to provide individual feedback and also, group the students based on their learning skills. Like on average, learners are good at remembering the syntax and concepts, mediocre in logical and critical thinking, and need more practice in code optimization and designing applications. Recommendations for Practitioners: The practical implications of this work include rubric designing for objective assessments and building an informative feedback process. Faculty can use this approach as an alternative assessment measure. They are the strong pillars of e-assessments and virtual learning platforms. Recommendation for Researchers: This research presents a novel approach to rubric-based objective assessments. Thus, it provides a fresh perspective to the researchers promising enough opportunities in the current era of digital education. Impact on Society: In order to accomplish the shared objective of reflective learning, the grading rubric and its accompanying analysis can be utilized by both instructors and students. As an instructional assessment tool, the rubric helps instructors to align their pedagogies with the students’ learning levels and assists students in updating their learning paths based on the informative topic-wise scores generated with the help of the rubric. Future Research: The designed rubric in this study can be extended to other programming languages and subjects. Further, an adaptable weighted rubric can be created to execute a flexible and reflective learning process. In addition, outcome-based learning can be achieved by measuring and analyzing student improvements after rubric evaluation.

Aim/Purpose: To encourage students’ engagement in peer assessments and provide students with better-quality feedback, this paper describes a technique for author-reviewer matching in peer assessment systems – a Balanced Allocation algorithm. Background: Peer assessment concerns evaluating the work of colleagues and providing feedback on their work. This process is widely applied as a learning method to involve students in the progress of their learning. However, as students have different ability levels, the efficacy of the peer feedback differs from case to case. Thus, peer assessment may not provide satisfactory results for students. In order to mitigate this issue, this paper explains and evaluates an algorithm that matches the author to a set of reviewers. The technique matches authors and reviewers based on how difficult the authors perceived the assignment to be, and the algorithm then matches the selected author to a group of reviewers who may meet the author’s needs in regard to the selected assignment. Methodology: This study used the Multiple Criteria Decision-Making methodology (MCDM) to determine a set of reviewers from among the many available options. The weighted sum method was used because the data that have been collected in user profiles are expressed in the same unit. This study produced an experimental result, examining the algorithm with a real collected dataset and mock-up dataset. In total, there were 240 students in the real dataset, and it contained self-assessment scores, peer scores, and instructor scores for the same assignment. The mock-up dataset created 1000 records for self-assessment scores. The algorithm was evaluated using focus group discussions with 29 programming students and interviews with seven programming instructors. Contribution: This paper contributes to the field in the following two ways. First, an algorithm using a MCDM methodology was proposed to match authors and reviewers in order to facilitate the peer assessment process. In addition, the algorithm used self-assessment as an initial data source to match users, rather than randomly creating reviewer – author pairs. Findings: The findings show the accurate results of the algorithm in matching three reviewers for each author. Furthermore, the algorithm was evaluated based on students’ and instructors’ perspectives. The results are very promising, as they depict a high level of satisfaction for the Balanced Allocation algorithm. Recommendations for Practitioners: We recommend instructors to consider using the Balanced Allocation algorithm to match students in peer assessments, and consequently to benefit from personalizing peer assessment based on students' needs. Recommendation for Researchers: Several MCDM methods could be expanded upon, such as the analytic hierarchy process (AHP) if different attributes are collected, or the artificial neural network (ANN) if fuzzy data is available in the user profile. Each method is suitable for special cases depending on the data available for decision-making. Impact on Society: Suitable pairing in peer assessment would increase the credibility of the peer assessment process and encourage students’ engagement in peer assessments. Future Research: The Balanced Allocation algorithm could be applied using a single group, and a peer assessment with random matching with another group may also be conducted, followed by performing a t-test to determine the impact of matching on students’ performances in the peer assessment activity.

Aim/Purpose: This research aims to describe layering of career-like experiences over existing curriculum to improve perceived educational value. Background: Feedback from students and regional businesses showed a clear need to increase student’s exposure to career-like software development projects. The initial goal was to develop an instructor-optional project that could be used in a single mid-level programming course; however, the pilot quickly morphed into a multi-year study examining the feasibility of agile projects in a variety of settings. Methodology: Over the course of four years, an agile project was honed through repeated Design Based Research (DBR) cycles of design, implementation, testing, communication, and reflective analysis. As is common with DBR, this study did not follow single methodology design; instead, analysis of data coupled with review of literature led to exploration and testing of a variety of methodologies. The review phase of each cycle included examination of best practices and methodologies as determined by analysis of oral and written comments, weekly journals, instructor feedback, and surveys. As a result of participant feedback, the original project was expanded to a second project, which was tested in another Software Engineering (SE) course. The project included review and testing of many academic and professional methodologies, such as Student Ownership of Learning, Flipped Classroom, active learning, waterfall, agile, Scrum, and Kanban. The study was homogenous and quasi-experimental as the population consisted solely of software engineering majors taking required courses; as based on validity of homogenous studies, class sizes were small, ranging from 8 to 20 students. Close interactions between respondents and the instructor provided interview-like settings and immersive data capture in a natural environment. Further, the iterative development practices of DBR cycles, along with the inclusion of participants as active and valued stakeholders, was seen to align well with software development practitioner practices broadly known as agile. Contribution: This study is among the first to examine layering a career-like software development project on top of a course through alteration of traditional delivery, agile development, and without supplanting existing material. Findings: In response to industry recommendations for additional career-like experiences, a standalone agile capstone-like project was designed that could be layered over an existing course. Pilot data reflected positive perceptions of the project, although students did not have enough time to develop a working prototype in addition to completing existing course materials. Participant feedback led to simultaneous development of a second, similar project. DBR examination of both projects resulted in a simplified design and the ability to develop a working prototype, if and only if the instructor was willing to make adjustments to delivery. After four years, a solution was developed that is both stable and flexible. The solution met the original charge in that it required course delivery, not course material, to be adjusted. It is critical to note that when a working prototype is desired, a portion of the lecture should be flipped allowing more time for guided instruction through project-focused active learning and study group requirements. The results support agile for standalone software development projects, as long as passive delivery methods are correspondingly reduced. Recommendations for Practitioners: Based on the findings, implementation of a career-like software development project can be well received as long as active learning components are also developed. Multiple cycles of DBR are recommended if future researchers wish to customize instructional delivery and develop complex software development projects. Programming instructors are recommended to explore hybrid delivery to support development of agile career-like experiences. Small class sizes allowed the researchers to maintain an interview-like setting throughout the study and future studies with larger classes are recommended to include additional subject matter experts such as graduate students as interaction with a subject matter expert was highly valued by students. Recommendation for Researchers: Researchers are recommended to further examine career-like software development experiences that combine active learning with agile methods; more studies following agile and active learning are needed to address the challenges faced when complex software development is taught in academic settings. Further testing of standalone agile project development has now occurred in medium sized in person classes, online classes, independent studies, and creative works research settings; however, further research is needed. Future research should also examine the implementation of agile projects in larger class sizes. Increasing class size should be coupled with additional subject matter experts such as graduate students. Impact on Society: This study addresses professional recommendations for development of agile career-like experiences at the undergraduate level. This study provides empirical evidence of programming projects that can be layered over existing curriculum, with no additional cost to the students. Initial feedback from local businesses and graduates, regarding agile projects with active learning, has been positive. The area business that refused to hire our underprepared SE graduates has now hired several. Future Research: Future research should explore layering agile projects over a broader range of software development courses. Feedback from hiring professionals and former students has been positive. It is also recommended that DBR be used to develop career-like experiences for online programming courses.

Aim/Purpose: The study focused on learner sentiments and experiences after using the Moodle assessment module and trained a machine learning classifier for future sentiment predictions. Background: Learner assessment is one of the standard methods instructors use to measure students’ performance and ascertain successful teaching objectives. In pedagogical design, assessment planning is vital in lesson content planning to the extent that curriculum designers and instructors primarily think like assessors. Assessment aids students in redefining their understanding of a subject and serves as the basis for more profound research in that particular subject. Positive results from an evaluation also motivate learners and provide employment directions to the students. Assessment results guide not just the students but also the instructor. Methodology: A modified methodology was used for carrying out the study. The revised methodology is divided into two major parts: the text-processing phase and the classification model phase. The text-processing phase consists of stages including cleaning, tokenization, and stop words removal, while the classification model phase consists of dataset training using a sentiment analyser, a polarity classification model and a prediction validation model. The text-processing phase of the referenced methodology did not utilise tokenization and stop words. In addition, the classification model did not include a sentiment analyser. Contribution: The reviewed literature reveals two major omissions: sentiment responses on using the Moodle for online assessment, particularly in developing countries with unstable internet connectivity, have not been investigated, and variations of the k-fold cross-validation technique in detecting overfitting and developing a reliable classifier have been largely neglected. In this study we built a Sentiment Analyser for Learner Emotion Management using the Moodle for assessment with data collected from a Ghanaian tertiary institution and developed a classification model for future sentiment predictions by evaluating the 10-fold and the 5-fold techniques on prediction accuracy. Findings: After training and testing, the RF algorithm emerged as the best classifier using the 5-fold cross-validation technique with an accuracy of 64.9%. Recommendations for Practitioners: Instead of a closed-ended questionnaire for learner feedback assessment, the open-ended mechanism should be utilised since learners can freely express their emotions devoid of restrictions. Recommendation for Researchers: Feature selection for sentiment analysis does not always improve the overall accuracy for the classification model. The traditional machine learning algorithms should always be compared to either the ensemble or the deep learning algorithms Impact on Society: Understanding learners’ emotions without restriction is important in the educational process. The pedagogical implementation of lessons and assessment should focus on machine learning integration Future Research: To compare ensemble and deep learning algorithms

This research aims to establish a valid and accurate measurement scale and identify consumer-driven characteristics for minimalism. The study has employed a hybrid approach to produce items for minimalism. Expert interviews were conducted to identify the items for minimalism in the first phase followed by consumer survey to obtain their response in second phase. A five-point Likert scale was used to collect the data. Further, data was subjected to reliability and validity check. Structural equation modelling was used to test the model. The findings demonstrated that there are five dimensions by which consumers perceive minimalism: decluttering, mindful consumption, aesthetic choices, financial freedom, and sustainable lifestyle. The outcome also revealed a high correlation between simplicity and well-being. This study is the first to provide a reliable and valid instrument for minimalism. The results will have several theoretical and practical ramifications for society and policymakers. It will support policymakers in gauging and encouraging minimalistic practices, which enhance environmental performance and lower carbon footprint.

This research investigates the correlation between risk management and supply chain performance (SCP) along with moderation of AI-embedded technologies such as big data analytics, Internet of Things (IoT), virtual reality, and blockchain technologies. To calculate the results, this study utilised 644 questionnaires through the structural equation modelling (SEM) method. It is revealed using SmartPls that financial risk management (FRM) is positively linked with SCP. Second, it was observed that AI significantly moderates the connection between FRM and SCP. In addition, the study presents certain insights into supply chain and AI-enabled technologies and how these capabilities can beneficially advance SCP. Besides, certain implications, both managerial and theoretical are described for the supply chain managers along with limitations for future scholars of the world.

Students in teaching-focused business-schools need a level of assistance and advisement broader and more profound than what is needed in R1&R2 schools. We investigate the informal interdependencies among marketing, finance, operation, and management core courses in these schools. By conducting hypothesis tests on a large dataset, we identify a flexible network showing the preferred sequencing of these courses to improve students' performance as measured by the course grade. Better performances in this context may also lead to higher retention-rates and lower time-to-degree. We recommend taking Finance or Finance and Management as the first course(s). Marketing should be the next course before or concurrent with Operations Management. Regarding the lower division courses, it is recommended to take Statistics before Economics and Accounting courses and Accounting before or concurrent with Economics. We also consider the significant role of a milestone course that links the lower division and core courses.

In order to improve the classification accuracy and online allocation accuracy of teaching resources and shorten the allocation time, this paper proposes a new online allocation method of college ideological and political curriculum teaching resources based on differential search algorithm. Firstly, the feedback parameter model of teaching resources cleaning is constructed to complete the cleaning of teaching resources. Secondly, according to the results of anti-interference consideration, the linear feature extraction of ideological and political curriculum teaching resources is carried out. Finally, the online allocation objective function of teaching resources for ideological and political courses is constructed, and the differential search algorithm is used to optimise the objective function to complete the online allocation of resources. The experimental results show that this method can accurately classify the teaching resources of ideological and political courses, and can shorten the allocation time, with the highest allocation accuracy of 97%.

In view of the problems of low accuracy, long time consuming and low efficiency of the existing engineering investment risk assessment method; this paper puts forward the investment risk assessment method of power grid construction project based on grey correlation analysis. Firstly, classify the risks of power grid construction project; secondly, determine the primary index and secondary index of investment risk assessment of power grid construction project; then construct the correlation coefficient matrix of power grid project investment risk to calculate the correlation degree and weight of investment risk index; finally, adopt the grey correlation analysis method to construct investment risk assessment function to realise investment risk assessment. The experimental results show that the average accuracy of evaluating the investment risk of power grid construction projects using the method is 95.08%, and the maximum time consuming is 49 s, which proves that the method has high accuracy, short time consuming and high evaluation efficiency.

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.