The goal of this study was to examine the effects of task-related variables, such as the difficulty level, problem scenario, and experiment week, on performance and mental workload of 27 healthy adult subjects during problem solving within the spatial navigation transfer (SNT) game. The study reports task performance measures such as total time spent on a task (TT) and reaction time (RT); neurophysiological measures involving the use of functional near-infrared spectroscopy (fNIRS); and a subjective rating scale for self-assessment of mental workload (NASA TLX) to test the related hypothesis. Several within-subject repeated-measures factorial ANOVA models were developed to test the main hypothesis. The results revealed a number of interaction effects for the dependent measures of TT, RT, fNIRS, and NASA TLX. The results showed (1) a decrease in TT and RT across the three levels of difficulty from Week 1 to Week 2; (2) an increase in TT and RT for high and medium cognitive load tasks as compared to low cognitive load tasks in both Week 1 and Week 2; (3) an overall increase in oxygenation from Week 1 to Week 2. These findings confirmed that both the behavioral performance and mental workload were sensitive to task manipulations.

Transfer of knowledge, skills, and experience is critical in an increasingly competitive knowledge-based global economy. Research indicates major issues relating to transfer of learning, including (a) the complex nature of transfer, (b) the multiple variables affecting transfer, and (c) the limited knowledge of instructional methodologies for facilitating transfer across disciplines and learning environments. An integrative literature review was conducted to analyze the conceptualizations of transfer of learning across disciplines, as well as to examine the traditional and contemporary models along with taxonomies of transfer. This article proposes a new Integrative Transfer of Learning (ITL) model that aggregates four broad transfer dimensions, specifically (a) task, (b) personal, (c) context, and (d) pedagogical dimensions. This ITL model provides a comprehensive conceptual framework for researchers, instructors, and instructional designers interested in transfer of learning across learning environments, including online, blended, and onsite, for preparing a diverse higher education student population for a complex and advancing workforce.

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Institutions of higher education play a critical role in bridging academia and workforce, yet college students find it challenging to transfer their learning across and beyond instructional formats, including online, hybrid, and face-to-face. The goals of this exploratory, sequential, mixed-methods study were to (1) explore graduate students’ conceptualizations of transfer, and (2) examine online pedagogical practices for enhancing transfer. Participants included students enrolled in a full-time online graduate degree program in education at a private university in the Mid-Atlantic USA. Findings from the qualitative phase with seven semi-structured interviews were used to design a survey study with 68 graduate students to explore their perceptions of effective online pedagogical practices for enhancing transfer. This study is significant since its findings revealed a number of online practices that instructional designers and faculty can use to optimize learning and transfer in higher education.

Spatial visualization ability (SVA) has been identified as a potential key factor for academic achievement and student retention in Science, Technology, Engineering, and Mathematics (STEM) in higher education, especially for engineering and related disciplines. Prior studies have shown that training using virtual reality (VR) has the potential to enhance learning through the use of more realistic and/or immersive experiences. The aim of this study was to investigate the effect of VR-based training using spatial visualization tasks on participant performance and mental workload using behavioral (i.e., time spent) and functional near infrared spectroscopy (fNIRS) brain-imaging-technology-derived measures. Data were collected from 10 first-year biomedical engineering students, who engaged with a custom-designed spatial visualization gaming application over a six-week training protocol consisting of tasks and procedures that varied in task load and spatial characteristics. Findings revealed significant small (Cohen’s d: 0.10) to large (Cohen’s d: 2.40) effects of task load and changes in the spatial characteristics of the task, such as orientation or position changes, on time spent and oxygenated hemoglobin (HbO) measures from all the prefrontal cortex (PFC) areas. Transfer had a large (d = 1.37) significant effect on time spent and HbO measures from right anterior medial PFC (AMPFC); while training had a moderate (d = 0.48) significant effect on time spent and HbR measures from left AMPFC. The findings from this study have important implications for VR training, research, and instructional design focusing on enhancing the learning, retention, and transfer of spatial skills within and across various VR-based training scenarios.