Open Materials Discourse: Enhancement of Recall within Technology-Mediated Teams Through the Use of Online Visual Artifacts

This paper provides the materials used to conduct the Basoglu, Fuller, and Valacich (2012) study of individuals’ recall of information within technology-mediated teams (i.e., virtual teams). In the Basoglu et al. (2012) study, three input factors—visual artifacts (i.e., a computer-generated image of each team member), team size, and work interruptions—were manipulated to assess their influence on a person’s ability to recall important characteristics of their virtual team members. In the current paper, we provide step-by-step instructions for the experimental design, procedures, consent form, and the questionnaire administered by Basoglu et al. (2012). Our objectives are to provide researchers with the necessary materials to replicate the Basoglu et al. (2012) study and use its methodological techniques to guide their own research

Innovations in Teaching the Information Systems Curriculum

College students today make up a population that is highly diverse, with values that are often different from the professors. As educators, we are all faced with the question of How can we effectively teach these students? This panel proposes to explore several innovative approaches and techniques that have been successfully integrated into the panelists\u27 courses. These techniques include introducing technology, critical thinking, collaborative learning, and experiential learning. Our goal is to provide concrete suggestions that the audience can take with them and integrate across the IS curriculum. Each panelist willpresent an overview of the particular technique they are using, and summarize how others could integrate similar processes into their classes. The panelists represent the range of research, teaching, and research/teaching institutions. Additionally the techniques have been integrated into both graduate and undergraduate courses. The panelists\u27 proposals are summarized belo

How Online Patient–Physician Interaction Influences Patient Satisfaction

Online health interaction (OHI) is an effective and increasingly popular method for patients to access health information. Extant literature overlooks such service users’ satisfaction derived from online interactions and the measurement of OHI processes. Based on the relational communication literature and the features of OHI, the present study proposes three dimensions to conceptualize the success of OHI processes (i.e., interaction depth, information intensity, and time breadth) and explores the association between these interaction processes and service satisfaction. Further, two characteristics of OHI, namely information richness and indirect interaction, are identified as contingent factors on those proposed linkages. The research model was tested on the objective data collected from an online healthcare platform. The study findings showed that (1) interaction depth, information intensity, and time breadth positively impact service satisfaction and (2) both information richness and indirect interaction negatively moderate the effects of interaction depth and information intensity and positively moderate the effect of time breadth. The present study contributes to the existing literature by conceptualizing online interaction process and identifying the role of the specific characteristics of online healthcare and also provides implications to practitioners

Negative emotions influence how we move the computer mouse

Finding offers game-changing options for businesses, insider-threat detection and national security, write Martin Hibbeln, Jeffrey Jenkins, Christoph Schneider, Joe Valacich and Markus Weinman

Detecting Users’ Psychological States through Mouse Cursor Movements

Behavioral research in information systems is testing increasingly complex models using sophisticated statistical methodologies. As the inputs into these models are often unobservable constructs, they are subject to various biases such as social desirability or demand effects. Responding to such problems, IS researchers have recently turned to the use of psychophysiological tools to get a deeper understanding of the constructs of interest. However, such tools also have a number of drawbacks, such as high costs or increased artificiality of the setting, potentially limiting external validity. To this end, we propose augmenting the use of traditional measurement scales and psychophysiological tools with other, readily observable phenomena. As a case in point, we propose mouse cursor movements as having the potential to provide online retailers with possibilities to infer users’ state of flow, and discuss the potential of using mouse cursor movements for inferring users’ psychological states in other settings and context

Improving the Quality of Survey Data: Using Answering Behavior as an Alternative Method for Detecting Biased Respondents

Online surveys are used for collecting self-report data. Despite their prevalent use, data quality problems persist due to various response biases. Here, we demonstrate how participant answering behaviors can be used to identify biased responses. We administered an online survey where participants reported their personality dimensions of neuroticism and extraversion—two personality dimensions that have been previously shown to be correlated with a propensity to deceive—and were later presented with a scenario to exhibit deceptive behavior. We then generated models to predict deception using the neuroticism and extraversion constructs. Using respondents’ fine-grained mouse movement data when answering these questions, we generated time, behavior, and navigation-based metrics to identify biased participants. By removing these outliers, model performance improved by 93% for neuroticism and 10% for extraversion. This approach aids in gaining a clearer understanding of how some types of response biases influence model performanc

Creating a Realistic Experimental Scenario for HCI-Based Deception Detection Research with Ground Truth and Unsanctioned Malicious Acts

This research-in-progress note reports on the design and execution of a study in HCI-based deception detection. The objective of the study is to examine the impact of knowledge of tracking and countermeasures on the neuro- motor changes detected when subjects commit a malfeasant act. To examine this, an experimental context and design was required that would afford the subjects an opportunity to commit an un-sanctioned malicious act while tracking ground truth in an unobtrusive manner. The experimental design, study execution, and preliminary results are presented