End-user training methods

Explore to Learn

Explorative information systems behaviors are the ways in which individuals actively revise their usage and discover creative means of applying the system, extending the potentials of the system, and enhancing task performance. This study has developed a specific concept of explorative system behavior-explorative information technology (IT) learning-to describe users' post-training learning behavior-novel use. Adapting a herding lens, we study the individual and team-level triggers of explorative learning cognitions. The study tests the proposed cross-level model and collects data from 225 individuals who are divided into 51 teams. The results indicate that individuals tend to innovatively use a system through developed exploration cognitions in team settings as a response to examined herd behavior triggers. The study uncovered that members of cohesive teams and learners with high uncertainty perceptions are more likely to imitate the observed explorative learning behaviors of their peers and reproduce such behaviors in the long term.

Bridging the Digital Divide for Older Adults via Observational Training: Effects of Model Identity from a Generational Perspective

The proliferation of technology offers potential solutions for enhancing the well-being of older adults. However, older adults often have low digital literacy and are disengaged from the digital world. With age-appropriate training, older adults are expected to acquire a wide range of technological skills and bridge the digital divide. Through the lens of social cognitive theory, this study aims to investigate the effectiveness of observational training through behavior modeling in enhancing technology acceptance in older adults. The moderating effects of model identity on training outcomes from a generational perspective are examined. An empirical training experiment was completed with 59 community-dwelling older adults. Training outcomes were measured using cognitive knowledge, affective variables, and meta-cognition. The results ascertain the effectiveness of observational training in improving their technological knowledge, self-efficacy, outcome expectations, and sense of social connectedness when using technologies. From a generational perspective, the older adult behavior model is more effective than the young or child behavior models in increasing self-efficacy and willingness to use technology. The model identity further enhances the positive outcomes of training. The results of this study contribute to designing educational interventions to bridge the digital divide.

A Revision of Computer Self-Efficacy Conceptualizations in Information Systems

Computer self-efficacy is one of the more important constructs in information systems (IS) research. Over the years, IS researchers have debated about its multifaceted nature. Yet, despite, extensive debate, we contend that for information systems, the conceptualization of various self-efficacy dimensions is incomplete. The primary dimension currently focused on is the specificity of the technology. This has resulted in two types of self-efficacy being investigated: computer self-efficacy and specific computer self-efficacy. However, the task being performed with technology has received limited attention in information systems self-efficacy research and discussions. We argue that there are four distinct types of computer self-efficacy constructs that are derived from combining the dimensions of specificity of information technology (specific/general) and task type (simple/complex) into a 2x2 model. Using data gathered from a quasi-experimental study, we illustrate how these constructs are not only theoretically different but also have a distinct measurement item set. Implications for expanding self-efficacy research are discussed at the end.

Author Highlights for the Past 35 Years

This essay reviews leading contributions to The DATA BASE for Advances in Information Systems over the past 35 years, both in terms of identifying leading scholars who published most frequently in the journal as well as papers that have been cited most frequently. Using standard scientometric methods, I identify the leading authors who published five or more papers since 1982. In terms of analyzing highly cited papers, I organize the analysis into four time periods of nine years each, a structure that reveals that The DATA BASE has been a longstanding venue for IS scholars to introduce their early work - whether conceptual or empirical. Notably, several esteemed IS scholars published early conceptual versions of their ideas in The DATA BASE - often many years before they followed up with related work in other journals. In terms of highly cited papers, the analysis in this essay also reveals that The DATA BASE shifted toward publishing empirical papers after 1990 and, despite the prevalence of positivist, quantitative research during the past 25 years, qualitative research has also become prominent in the journal. More recently, the journal has also featured several literature review papers on important topic areas, such as virtual teams, technostress, IT outsourcing, and IT security. This essay reviews leading contributions to The DATA BASE for Advances in Information Systems over the past 35 years, both in terms of identifying leading scholars who published most frequently in the journal as well as papers that have been cited most frequently. Using standard scientometric methods, I identify the leading authors who published five or more papers since 1982. In terms of analyzing highly cited papers, I organize the analysis into four time periods of nine years each, a structure that reveals that The DATA BASE has been a longstanding venue for IS scholars to introduce their early work - whether conceptual or empirical. Notably, several esteemed IS scholars published early conceptual versions of their ideas in The DATA BASE - often many years before they followed up with related work in other journals. In terms of highly cited papers, the analysis in this essay also reveals that The DATA BASE shifted toward publishing empirical papers after 1990 and, despite the prevalence of positivist, quantitative research during the past 25 years, qualitative research has also become prominent in the journal. More recently, the journal has also featured several literature review papers on important topic areas, such as virtual teams, technostress, IT outsourcing, and IT security.

Process is King: Evaluating the Performance of Technology-mediated Learning in Vocational Software Training

Technology-mediated learning (TML) is a major trend in education, since it allows to integrate the strengths of traditional- and IT-based learning activities. However, TML providers still struggle in identifying areas for improvement in their TML offerings. One reason for their struggles is inconsistencies in the literature regarding drivers of TML performance. Prior research suggests that these inconsistencies in TML literature might stem from neglecting the importance of considering the process perspective in addition to the input and outcome perspectives. This gap needs to be addressed to better understand the different drivers of the performance of TML scenarios. Filling this gap would further support TML providers with more precise guidance on how to (re-)design their offerings toward their customers’ needs. To achieve our goal, we combine qualitative and quantitative methods to develop and evaluate a holistic model for assessing TML performance. In particular, we consolidate the body of literature, followed by a focus group workshop and a Q-sorting exercise with TML practitioners, and an empirical pre-study to develop and initially test our research model. Afterward, we collect data from 161 participants of TML vocational software trainings and evaluate our holistic model for assessing TML performance. The results provide empirical evidence for the importance of the TML process quality dimension as suggested in prior literature and highlighted by our TML practitioners. Our main theoretical as well as practical contribution is a holistic model that provides comprehensive insights into which constructs and facets shape the performance of TML in vocational software trainings.

Do I Matter?

Advances in technology-mediated learning (TML) have created opportunities to personalize learning, based on the assumption that individual differences affect one's ability to learn. However, cumulative research on individual differences is equivocal, and largely excludes the learning process. The authors argue that without a model that incorporates the process of learning, the authors cannot empirically assess how individual differences influence learning outcomes. This study first models the learning process in terms of two sub-processes: process appropriation and content assimilation. Second, it partially tests the model within a technology-mediated learning (TML) environment used to provide end-user IT training. The results support the efficacy of individual differences' influence on learning outcomes, while shedding light on how this effect occurs. Individual differences affect the appropriation of TML supplied structures, which in turn impacts learning outcomes. The research method used in the study is a laboratory experiment. Data was analyzed using SEM.