The role of regulation in medical student learning in small groups: Regulating oneself and others’ learning and emotions

This study examines the role of regulatory processes in medical students as they learn to deliver bad news to patients in the context of an international web-based problem based learning environment (PBL). In the PBL a medical facilitator and students work together to examine video cases on giving bad news and share their perspectives on what was done effectively and what could be done differently. We examine how regulation occurs within this collaboration. A synchronous computer-supported collaborative learning environment (CSCL) facilitated peer discussion at a distance using a combination of tools that included video-conferencing, chat boxes, and a shared whiteboard to support collaborative engagement. We examine regulation along a continuum, spanning from self- to co-regulation, in situations where medical students learn how to manage their own emotions and adapt their responses to patient reactions. We examine the nature of the discourse between medical students and facilitators to illustrate the conditions in which metacognitive, co-regulation and social emotional activities occur to enhance learning about how to communicate bad news to patients.     

Machine learning advice in managerial decision-making: The overlooked role of decision makers’ advice utilization

Machine learning (ML) analyses offer great potential to craft profound advice for augmenting managerial decision-making. Yet, even the most promising ML advice cannot improve decision-making if it is not utilized by decision makers. We therefore investigate how ML analyses influence decision makers’ utilization of advice and resulting decision-making performance. By analyzing data from 239 ML-supported decisions in real-world organizational scenarios, we demonstrate that decision makers’ utilization of ML advice depends on the information quality and transparency of ML advice as well as decision makers’ trust in data scientists’ competence. Furthermore, we find that decision makers’ utilization of ML advice can lead to improved decision-making performance, which is, however, moderated by the decision makers’ management level. The study’s results can help organizations leverage ML advice to improve decision-making and promote the mutual consideration of technical and social aspects behind ML advice in research and practice as a basic requirement.     

Augmented reality in language learning: A state-of-the-art review of 2014–2019

This systematic review study synthesizes research findings pertaining to the use of augmented reality (AR) in language learning. Published research from 2014 to 2019 has been explored and specific inclusion and exclusion criteria have been applied resulting in 54 relevant publications. Our findings determined: (a) devices and software employed for mastering AR; languages and contexts in which AR had been applied; theoretical perspectives adopted for guiding the use of AR; the number of participants in AR activities and benefits from using AR as an educational tool in the language classroom; (b) alignment of the affordances of Augmented Reality with the KSAVE (Knowledge, Skills, Attitudes, Values, Ethics) 21st-century skills framework; (c) future directions in AR research and practice. The main findings from this review demonstrate the popularity of mobile-based AR for supporting vocabulary (23.9%), reading (12.7%), speaking (9.9%) writing (8.5%) or generic language skills (9.9%). Our findings also uncovered areas that merit future attention in the application of AR in language learning – for instance learning theories were not often considered in the implementation of AR. The study concludes with suggestions for future research especially in the areas of instructional design and user experience.     

Crossing boundaries in Facebook: Students’ framing of language learning activities as extended spaces

Young people’s interaction online is rapidly increasing, which enables new spaces for communication; the impact on learning, however, is not yet acknowledged in education. The aim of this exploratory case study is to scrutinize how students frame their interaction in social networking sites (SNS) in school practices and what that implies for educational language teaching and learning practices. Analytically, the study departs from a sociocultural perspective on learning, and adopts conceptual distinctions of frame analysis. The results based on ethnographic data from a Facebook group in English-learning classes, with 60 students aged between 13 and 16 from Colombia, Finland, Sweden and Taiwan indicate that there is a possibility for boundary crossing, which could generate extended spaces for collaborative language-learning activities in educational contexts where students combine their school subject of learning language and their communicative use of language in their everyday life. Such extended spaces are, however, difficult to maintain and have to be recurrently negotiated. To take advantage of young people’s various dynamic communicative uses of language in their everyday life in social media, the implementation of such media for educational purposes has to be deliberately, collaboratively and dynamically negotiated by educators and students to form a new language-learning space with its own potentials and constraints.     

Partial evaluation of metaprograms in a “multiple worlds” logic language

This paper describes a partial evaluation system specifically designed to be used as an automatic compilation tool for metaprograms in a KBMS (EPSILON) based on Prolog. EPSILON main underlying concepts are the extension of Prolog with theories (“multiple worlds”) and the use of metaprogramming as the basic technique to define new inference engines and tools. Our partial evaluator is oriented towards theories and metainterpreter specialization. Being designed to be used as an automatic compiler, it does not require declarations from the user to control the unfolding process. It handles full Prolog and provides also an elegant solution to the problem of the partial evaluation of incomplete and self-modifying programs, by exploiting the multiple worlds feature added to Prolog. EPSILON partial evaluation system turned out to be a very useful and powerful tool to combine the low cost and the flexibility of metaprogramming with the performance requirements of a practical knowledge based system.     

A quantitative multimodal discourse analysis of teaching and learning in a web-conferencing environment – The efficacy of student-centred learning designs

This paper presents a quantitative approach to multimodal discourse analysis for analyzing online collaborative learning. The coding framework draws together the fields of systemic functional linguistics and Activity Theory to analyze interactions between collaborative-, content- and technology-related discourse. The approach is used to examine how the task subject matter, the activity design, and the choice of interface affected interaction and collaboration for a computing course conducted in a web-conferencing environment. The analysis revealed the critical impact of activity design on the amount and type of discourse that transpired. Student-centred designs resulted in over six times more student discourse as compared to teacher-centred designs and created a learning environment where students took greater ownership over the tasks and contributed more to the content-based discussion. The paper also incorporates a rationale for the approach to coding and a reflection on its efficacy for discourse analysis in technology-based learning environments.     

Synthetic speech in foreign language learning: an evaluation by learners

Can synthetic speech be utilized in foreign language learning as natural speech? In this paper, we evaluated synthetic speech from the viewpoint of learners in order to find out an answer. The results pointed out that learners do not recognize remarkable differences between synthetic voices and natural voices for the words with short vowels and long vowels when they try to understand the meanings of the sounds. The data explicates that synthetic voice utterances of sentences are easier to understand and more acceptable by learners compared to synthetic voice utterances of words. In addition, the ratings on both synthetic voices and natural voices strongly depend upon the learners’ listening comprehension abilities. We conclude that some synthetic speech with specific pronunciations of vowels may be suitable for listening materials and suggest that evaluating TTS systems by comparing synthetic speech with natural speech and building a lexical database of synthetic speech that closely approximates natural speech will be helpful for teachers to readily use many existing CALL tools.     

Simulation-based learning: The learning–forgetting–relearning process and impact of learning history

The results of empirical experiments evaluating the effectiveness and efficiency of the learning–forgetting–relearning process in a dynamic project management simulation environment are reported. Sixty-six graduate engineering students performed repetitive simulation-runs with a break period of several weeks between the runs. The students used a teaching tool called the project management trainer (PMT) that simulates a generic dynamic, stochastic project management environment. In this research, we focused on the effect of history recording mechanism on the learning forgetting process. Manual or automatic history recording mechanisms were used by the experimental group, while the control group did not use any history recording mechanism. The findings indicate that for the initial learning phase, the manual mechanism is better than the automatic mechanism. However, for the relearning phase, the break period length influenced the performance after the break. When the break period is short, the manual history keeping mechanism is better, but for a long period break, there is no significant difference. A comparison between the experimental group and the control group revealed that using any history recording mechanism reduced forgetting. Based on the findings, some practical implications of using simulators to improve the learning–forgetting process are discussed.     

The role of connection in the nonlinear behavior of locomotion systems with symmetry

Using a geometric framework, the role of connection in nonlinear behavior of locomotion systems with symmetry is investigated in this paper. It is shown that the covariant derivative of connection plays a fundamental role in describing the nonlinear behavior of locomotion systems with Lie group symmetries. In particular, by placing prescribed closed paths properly in the shape space, it is argued that the system will exhibit nonlinear behaviors such as limit cycles and bifurcation in the fiber. The idea is used to investigate nonlinear behavior of a three link fish-like articulated body in perfect fluid. Numerical results are presented showing limit cycles and other coherent gaits resulting from various locations of shape circle.     

The use of machine learning and deep learning algorithms in functional magnetic resonance imaging—A systematic review

Functional Magnetic Resonance Imaging (fMRI) is presently one of the most popular techniques for analysing the dynamic states in brain images using various kinds of algorithms. From the last decade, there is an exponential rise in the use of the machine and deep learning algorithms of artificial intelligence for analysing fMRI data. However, it is a big challenge for every researcher to choose a suitable machine or deep learning algorithm for analysing fMRI data due to the availability of a large number of algorithms in the literature. It takes much time for each researcher to know about the various approaches and algorithms which are in use for fMRI data. This paper provides a review in a systematic manner for the present literature of fMRI data that makes use of the machine and deep learning algorithms. The major goals of this review paper are to (a) identify machine learning and deep learning research trends for the implementation of fMRI; (b) identify usage of Machine Learning Algorithms and deep learning in fMRI, and (c) help new researchers based on fMRI to put their new findings appropriately in existing domain of fMRI research. The results of this systematic review identified various fMRI studies and classified them based on fMRI types, mental diseases, use of machine learning and deep learning algorithms. The authors have provided the studies with the best performance of machine learning and deep learning algorithms used in fMRI. The authors believe that this systematic review will help incoming researchers on fMRI in their future works.     

Automate or innervate? The role of knowledge in advanced manufacturing systems

This chapter examines the role of shopfloor knowledge in the operation of advanced manufacturing systems. Design trends towards full automation are contrasted with those toward hybrid, human-centred systems with particular emphasis on job design and the development and reproduction of knowledge. The chapter concludes with a short discussion of the problems inherent in hybrid design.Failure is most frequently from want of energy than want of capital Daniel Webster     

The role of IT in organizational innovation – A systematic literature review

Information technology (IT) is broadly recognized as an important element in organizational innovation, however there has been relatively little integration of Information Systems (IS) research on the role of IT in organizational innovation. Such integration is particularly important in view of recent calls to examine the evolving ontological nature of IT, wherein IT artifacts are now shaping physical reality. We systematically examine innovation-related literature published in the leading IS journals in the period between 2009 and 2020 and we identify and summarize the core theoretical discourses in this domain. We find that extant literature largely examines the role of IT in innovation at a high level of abstraction, focusing on IT investments and IT capabilities, and consequently precluding granular insights on who, what, when, where, how, and why in relation to organizational innovation. To address this limitation and to provide a structuring lens for future research, we develop the organizational innovation system framework which posits that actors, IT artifacts, actions and organizational context are the key elements in organizational innovation systems that require more granular examination to yield deeper insights on how information technology contributes to organizational innovation. We re-examine the literature through the organizational innovation system lens and we identify gaps in extant research. We also outline potential directions for expanding the scope of future research.     

Is role playing in Requirements Engineering Education increasing learning outcome?

Requirements Engineering has attracted a great deal of attention from researchers and practitioners in recent years. This increasing interest requires academia to provide students with a solid foundation in the subject matter. In Requirements Engineering Education (REE), it is important to cover three fundamental topics: traditional analysis and modeling skills, interviewing skills for requirements elicitation, and writing skills for specifying requirements. REE papers report about using role playing as a pedagogical tool; however, there is a surprising lack of empirical evidence on its utility. In this paper we investigate whether a higher grade in a role playing project have an effect on students’ score in an individual written exam in a Requirements Engineering course. Data are collected from 412 students between the years of 2007 and 2014 at Lund University and Chalmers | University of Gothenburg. The results show that students who received a higher grade in the role playing project scored statistically significant higher in the written exam compared to the students with a lower role playing project grade.     

The “problem” in and of management information systems

Management Information Systems uncritically draws upon a number of disciplines for its theoretical framework. In doing so it has imported a host of ontological, epistemological and behavioral assumptions which have shaped the theories, technologies and practices of information system analysis, design and implementation. This has taken place without careful reflection upon the historical emergence of these assumptions or upon the context within which attempts are made to operationalize them. This paper argues that the Management Information Systems field is in need of researching itself. It proposes that through a combination of genealogical and ethnographic research methodologies, the historical emergence of theoretical constructs and the organizational context within which information systems operate should be critically examined. In the following analysis, the historical emergence of the “problem” as a generic construct in the Management Information System literature is examined and contrasted to the manner in which a group of manufacturing managers defined problems within their organizational context. A critical tension is revealed which suggests that information systems researchers, analysts and designers need to at least broaden their assumption about the nature of organizational reality, human behavior, information processing and problem solving.     

The impact of IT–business strategic alignment on firm performance: The evolving role of IT in industries

This study proposes and validates a new industry taxonomy to understand the use of IT that generates superior economic returns based on the specific economic and competitive characteristics of four different industry types and the strategic role of IT in each of these industry environments. Our findings extend the well-established industry taxonomy on the strategic role of IT (Automate, Informate, Transform) by considering how IT is changing the nature of the product/service in industries where transformational logics prevail. We found that in industries where the product/service is digital in nature, the firms that achieve higher economic returns are those where IT is used to support dual strategies based on the integration of cost leadership and differentiation. Conversely, in other industries – with the exception of those producing commodities – the firms that achieve superior returns are those that use IT to support differentiation. The results of this study can help managers make intelligent decisions about competitive strategies and IT investments, depending on the business environment of the sector in which the firm operates and the generative potential of emerging technologies to do new things.     

Are visual programming languages better? The role of imagery in program comprehension

This paper presents one experiment to explain why and under which circumstances visual programming languages would be easier to understand than textual programming languages. Towards this goal we bring together research from psychology of programming and image processing. According to current theories of imagery processing imagery facilitates a quicker access to semantic information. Thus, visual programming languages should allow for quicker construction of a mental representation based on data flow relationships of a program than procedural languages. To test this hypothesis the mental models of C and spreadsheet programmers were assessed in different program comprehension situations. The results showed that spreadsheet programmers developed data flow based mental representations in all situations, while C programmers seemed to access first a control flow and then data flow based mental representations. These results could help to expand theories of mental models from psychology of programming to account for the effect of imagery.     

The role of disclosure of personal information in the evaluation of risk and trust in young peoples’ online interactions

This study examined the relationship between the evaluation of risk, trust and disclosure of personal information in young peoples’ online interactions. A series of 18 focus groups were conducted with young people aged 9–19 years old. The results suggested that the majority of young people have a high level of awareness of the risks and potential outcomes associated with their online behaviour. Participants perceived disclosure of personal information to be important for the development of online relationships, and discussed associated strategies for evaluating trust and verifying identity. The study suggests that the perceived benefits associated with the disclosure of personal information and interacting with ‘strangers’ online may outweigh the perceived risks associated with these behaviours as the result of the importance of peer relationships and the exploration of identity during adolescence. Identified age-related differences and similarities in relation to the themes are explored, and areas for future research discussed.