Abstract:Recent work suggests that technological devices and their use cannot be understood in isolation, and must be viewed as part of an artifact ecology. With the proliferation of information and communication technologies (ICTs), studying artifact ecologies is essential in order to design new technologies with effective affordances. This paper extends the discourse on artifact ecologies by examining how such ecologies are constructed in the context of mobile knowledge work, as sociotechnical arrangements that consi… Show more
“…As summarized in Figure 2 , applications in mobile devices are the most commonly reported learning tools in mobile learning ( Alioon and Delialioglu, 2015 ; Shorfuzzaman and Alhussein, 2016 ) of their diverse functionalities for learning activities ( Felisoni and Godoi, 2018 ; Jarrahi et al., 2017 ; Sobaih et al., 2016 ). Furthermore, some instructors have developed custom-made mobile learning applications for their own courses ( Parsazadeh et al., 2018 ).…”
Section: Resultsmentioning
confidence: 99%
“…In spite of the rapid pace of technological innovation, the available tools still pose barriers to mobile learning ( Figure 4 ), key barriers can be categorized into three groups, which are 1) technology-related problems ( Frank and Kapila, 2017 ; Jarrahi et al., 2017 ; Masters et al., 2016 ; Zhang et al., 2016 ), 2) basic skills in using mobile devices ( Crane et al., 2011 ; Jeno et al., 2017 ; Mori and Harada, 2010 ; Thomas and Fellowes, 2016 ), and 3) instructors’ attitude towards applying mobile devices in education ( Gikas and Grant, 2013 ; Pimmer et al., 2013 ). Figure 4 Barriers of mobile learning.…”
Section: Resultsmentioning
confidence: 99%
“…Another challenge that learners face is the network security of free Wi-Fi in public places ( Masters et al., 2016 ). Some learners mentioned problems related to the interface or general difficulties in using their devices ( Frank and Kapila, 2017 ); others noted inconveniences caused by accessories, such as short battery life ( Jarrahi et al., 2017 ; Masters et al., 2016 ). These problems may have to be solved to improve the applicability of devices or networks to mobile learning in the future.…”
Mobile devices are not only a tool for communication, but also a powerful instrument for the economy, mass communication, and learning. Because the use of mobile devices and the Internet is growing rapidly, these tools are increasingly being utilized in learning and instruction. It is therefore important to investigate how mobile devices can be applied in learning. This article focuses on analyzing the features of mobile learning as well as the barriers and influencing factors of using mobile devices in learning. It pays particular attention to clarifying the factors, techniques, and strategies that enhance learners' experiences in using mobile devices. It reports a systematic review that examined studies published in 2006–2018 containing the keywords “mobile learning” “m-learning”, “undergraduate students” and/or “higher education.” The results of the review indicated mobile devices can be used as learning tools for tasks such as submitting homework, reflecting on immediate learning experiences, and sharing ideas. Instructors should consider three main components in mobile learning: learners' and instructors’ readiness, learning management and supporting systems.
“…As summarized in Figure 2 , applications in mobile devices are the most commonly reported learning tools in mobile learning ( Alioon and Delialioglu, 2015 ; Shorfuzzaman and Alhussein, 2016 ) of their diverse functionalities for learning activities ( Felisoni and Godoi, 2018 ; Jarrahi et al., 2017 ; Sobaih et al., 2016 ). Furthermore, some instructors have developed custom-made mobile learning applications for their own courses ( Parsazadeh et al., 2018 ).…”
Section: Resultsmentioning
confidence: 99%
“…In spite of the rapid pace of technological innovation, the available tools still pose barriers to mobile learning ( Figure 4 ), key barriers can be categorized into three groups, which are 1) technology-related problems ( Frank and Kapila, 2017 ; Jarrahi et al., 2017 ; Masters et al., 2016 ; Zhang et al., 2016 ), 2) basic skills in using mobile devices ( Crane et al., 2011 ; Jeno et al., 2017 ; Mori and Harada, 2010 ; Thomas and Fellowes, 2016 ), and 3) instructors’ attitude towards applying mobile devices in education ( Gikas and Grant, 2013 ; Pimmer et al., 2013 ). Figure 4 Barriers of mobile learning.…”
Section: Resultsmentioning
confidence: 99%
“…Another challenge that learners face is the network security of free Wi-Fi in public places ( Masters et al., 2016 ). Some learners mentioned problems related to the interface or general difficulties in using their devices ( Frank and Kapila, 2017 ); others noted inconveniences caused by accessories, such as short battery life ( Jarrahi et al., 2017 ; Masters et al., 2016 ). These problems may have to be solved to improve the applicability of devices or networks to mobile learning in the future.…”
Mobile devices are not only a tool for communication, but also a powerful instrument for the economy, mass communication, and learning. Because the use of mobile devices and the Internet is growing rapidly, these tools are increasingly being utilized in learning and instruction. It is therefore important to investigate how mobile devices can be applied in learning. This article focuses on analyzing the features of mobile learning as well as the barriers and influencing factors of using mobile devices in learning. It pays particular attention to clarifying the factors, techniques, and strategies that enhance learners' experiences in using mobile devices. It reports a systematic review that examined studies published in 2006–2018 containing the keywords “mobile learning” “m-learning”, “undergraduate students” and/or “higher education.” The results of the review indicated mobile devices can be used as learning tools for tasks such as submitting homework, reflecting on immediate learning experiences, and sharing ideas. Instructors should consider three main components in mobile learning: learners' and instructors’ readiness, learning management and supporting systems.
“…Thus, the researchers explored the cognitive credibility and intellectual value associated with these terms as a means of conferring this credibility and intellectual renown on their respondents. Some examples of this practice may be given: “Data were collected from 640 employees working in three high‐technology companies in China” (Lee, Chiang, van Esch, & Cai, 2018, p. 1178); “through a questionnaire survey ( N = 366) of employees at five urban‐fringe science park business sites” (Colley, Brown, & Montarzino, 2017, p. 314); and “Our sample consisted of 36 MKWs, mostly drawn from North Carolina's Research Triangle” (Jarrahi, Nelson, & Thomson, 2017, p. 473); Volunteers—The researchers of 3 of the 124 articles (2.4%) worked with volunteers identified from records available on online platforms. Ford and Staples (2010) and Ford, Myrden, and Jones (2015) used the records of an online research support service (StudyResponse) that connects academic researchers and individuals who have volunteered to be contacted for academic research.…”
Section: Definition Of the Term Kw In The 223 Articles From The Samplementioning
Despite the strategic value of organizational knowledge as a source of sustainable competitive advantage, researchers have voiced their concern over the potential imprecision and undue use of the term “knowledge worker” in the relevant research literature. In order to identify the nature of this imprecision and discuss ways of overcoming addressing it, we analyzed 223 articles from diverse fields that make reference to the concept of “knowledge worker”. Applying content analysis, we analyzed the definitions identified and the types of worker considered by researchers to be knowledge workers. It was observed that the term ‘knowledge worker’ has been used for occupations and professions with different levels of complexity, including those that were mostly operational. In addition, we observed that the term ‘knowledge worker’ is used, in a majority of instances, without any definition being offered (67.7%). Subsequent semantic analysis of the set of actions attributed to knowledge workers aided in the identification of additional descriptors that assisted in the conceptualization the term. In the analyzes, the sole appearance of the verb exploit in an article in the field of Geography & Transport stood out, leading us to consider a link between the active work conducted by knowledge workers and the exploitation‐exploration dyad in accordance with the concepts of the fields of innovation and learning. The analysis of the article did not confirm our initial perception. After observing the non‐use of the exploitation‐exploration dyad in none of the definitions of the term knowledge worker in the 223 articles that were analyzed, and in the literatures cited in these articles, we considered this fact an opportunity for contribution. Therefore, this study presents the development of an innovative new definition for the term knowledge worker, associating it with actions of the exploration of organizational knowledge, whereas the term information worker is associated with actions of the exploitation of organizational knowledge. We close the discussions by addressing the impacts of these definitions for the practitioners and academics who work with the themes of knowledge management, organizational learning, core competences, and process management.
“…Mobile working arrangements present an extra layer of uncertainty and complexity, complicating the way by which artifact ecologies are constructed by individuals and employed to support their mobile knowledge work, requiring significant physical effort and planning for technological use . According to Jarrahi, Nelson and Thomson (2017), artifact ecologies are the ways by which users, as individuals or collectives, interact with and use multiple technologies, applications, and devices, for different purposes; the composition of the artifact ecology depends on emergent needs.…”
The emergence of globally distributed teams and the evolution of mobile technologies have increased the number of mobile knowledge workers (MKW). MKW are professionals who frequently work on the move, far from a fixed workplace, performing knowledge-intensive activities. MKW often work alone, which leads them to face constant challenges in their work practices and difficulties to get timely knowledge to solve their problems alone. Still, little is known about how the collaborative problem-solving is carried out in the MKW's context. To address this gap, we adopted the Design Science Research (DSR) as a research method, and we applied activity theory (AT) and expansive learning as theoretical foundations to understand the MKW's context. We created an artifact-a method implemented via a mobile app-to support collaborative problem-solving processes on the move, which allowed us to understand better how these processes occur, contributing not only to problems resolutions but also to organizational learning.
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