Analysing the Relationship Between Mental Load or Mental Effort and Metacomprehension Under Different Conditions of Multimedia Design

Cognitive load theory assumes effort may only lead to comprehension if the material-induced load leaves enough resources for learning processes. Therefore, multimedia materials should induce as little non-relevant load as possible. Metacognition research assumes that learners tap into their memory processes to generate a mental representation of their comprehension to regulate learning. However, when judging their comprehension, learners need to make inferences about actual understanding using cues such as their experienced mental load and effort during learning. Theoretical assumptions would assume both to affect understanding and its metacognitive representation (metacomprehension). However, the question remains how perceived effort and load are related to metacomprehension judgments while learning with multimedia learning material. Additionally, it remains unclear if this varies under different conditions of multimedia design. To better understand the relationship between perceived mental load and effort and comprehension and metacomprehension under different design conditions of multimedia material, we conducted a randomised between-subjects study (N = 156) varying the design of the learning material (text-picture integrated, split attention, active integration). Mediation analyses testing for both direct and indirect effects of mental load and effort on metacomprehension judgments showed various effects. Beyond indirect effects via comprehension, both mental load and effort were directly related to metacomprehension, however, this seems to vary under different conditions of multimedia design, at least for mental effort. As the direction of effect can only be theoretically assumed, but was not empirically tested, follow-up research needs to identify ways to manipulate effort and load perceptions without tinkering with metacognitive processes directly. Despite the limitations due to the correlative design, this research has implications for our understanding of cognitive and metacognitive processes during learning with multimedia.

Effect of the subjective intensity of fatigue and interoception on perceptual regulation and performance during sustained physical activity

Background The subjective experience of fatigue impairs an individual’s ability to sustain physical endurance performance. However, precise understanding of the specific role perceived fatigue plays in the central regulation of performance remains unclear. Here, we examined whether the subjective intensity of a perceived state of fatigue, pre-induced through prior upper body activity, differentially impacted performance and altered perceived effort and affect experienced during a sustained, isometric contraction in lower body. We also explored whether (cardiac) interoception predicted the intensity of experienced perceptual and affective responses and moderated the relationships between constructs during physical activity. Methods Using a repeated-measures study design, thirty male participants completed three experimental conditions, with the intensity of a pre-induced state of fatigue manipulated to evoke moderate (MOD), severe (SEV) and minimal (control; CON) intensity of perceptions prior to performance of the sustained contraction. Results Performance of the sustained contraction was significantly impaired under a perceived state of fatigue, with reductions of 10% and 14% observed in the MOD and SEV conditions, respectively. Performance impairment was accompanied by greater perceived effort and more negative affective valence reported during the contraction. However, effects were limited to comparisons to CON, with no difference evident between the two experimental trials (i.e. MOD vs. SEV). Individuals’ awareness of their accuracy in judging resting heartbeats was shown to predict the subjective intensity of fatigue experienced during the endurance task. However, interoception did not moderate the relationships evident between fatigue and both perceived effort and affective valence. Conclusions A perceived state of fatigue limits endurance performance, influencing both how effortful activity is perceived to be and the affective experience of activity. Though awareness of interoceptive representations of bodily states may be important to the subjective experience of fatigue, interoception does not modulate the relationships between perceived fatigue and other perceptual (i.e. effort) and affective constructs.

Development and testing of the aerial porter exoskeleton

Back pain is one of the largest drivers of workplace injury and lost productivity in industries around the world. Back injuries were one of the leading reasons in resulting in days away from work at 38.5% across all occupations, increasing for manual laborers to 43%. While the cause of the back pain can vary across occupations, for materiel movers it is often caused from repetitive poor lifting. To reduce the issues, the Aerial Porter Exoskeleton (APEx) was created. The APEx uses a hip-mounted, powered exoskeleton attached to an adjustable vest. An onboard computer calculates the configuration of the user to determine when to activate. Lift form is assisted by using a novel lumbar brace mounted on the sides of the hips. Properly worn, the APEx holds the user upright while providing additional hip torque through a lift. This was tested by having participants complete a lifting test with the exoskeleton worn in the “on” configuration compared with the exoskeleton not worn. The APEx has been shown to deliver 30 Nm of torque in lab testing. The activity recognition algorithm has also been shown to be accurate in 95% of tested conditions. When worn by subjects, testing has shown average peak reductions of 14.9% BPM, 8% in VO2 consumption, and an 8% change in perceived effort favoring the APEx.

Pharmacological blockade of muscle afferents and perception of effort: a systematic review with meta-analysis

The perception of effort (PE) provides information on task difficulty and influences physical exercise regulation and human behavior. This perception differs from other-exercise related perceptions such as pain. There is no consensus on the role of group III-IV muscle afferents as a signal processed by the brain to generate PE. The aim of this meta-analysis was to investigate the effect of pharmacologically blocking muscle afferents on the PE. Six databases were searched to identify studies measuring the ratings of perceived effort (RPE) during physical exercise, with and without pharmacological blockade of muscle afferents. Articles were coded based on the operational measurement used to distinguish studies in which PE was assessed specifically (effort dissociated) or as a composite experience including other exercise-related perceptions (effort not dissociated). Articles that did not provide enough information for coding were assigned to the unclear group. The effort dissociated group (n=6) demonstrated a slight RPE increase with reduced muscle afferents feedback (standard mean change raw (SMCR), 0.39; 95%CI, 0.13 to 0.64). The group effort not dissociated (n=2) did not reveal conclusive results (SMCR, -0.29; 95%CI, -2.39 to 1.8). The group unclear (n=8) revealed a slight RPE decrease with reduced muscle afferents feedback (SMCR, -0.27; 95%CI, -0.50 to -0.04). The heterogeneity in results between groups reveals that the inclusion of other perceptions than effort in its rating influences the RPE scores reported by the participants. The absence of decreased RPE in the effort dissociated group suggests that muscle afferents feedback is not a sensory signal generating PE.

Effects of Pause Design on the Decline in Pulling Effort and the Evaluation of Perceived Effort in Pulling Tasks

Pulling is one of the manual material handling activities that could lead to work-related musculoskeletal disorders. The objectives of this study were to explore the development of muscular fatigue when performing intermittent pulling tasks and to establish models to predict the pull strength decrease due to performing the tasks. A simulated truck pulling experiment was conducted. Eleven healthy male adults participated. The participants pulled a handle with a load of 40 kg, which resulted in a pulling force of approximately 123 N. The pulling tasks lasted for 9 or 12 min with one, two, or three pauses embedded. The total time period of the embedded pauses was 3 min. The pull strength after each pull and rest was measured. Ratings of the perceived exertion on body parts after each pull were also recorded. The results showed insignificant differences regarding the development of muscular fatigue related to rest frequency. We found that the development of muscular fatigue for pulling tasks with embedded pauses was significantly slower than that for continuous pulls. The forearm had a higher CR-10 score than the other body parts indicating that the forearm was the body part suffering early muscle fatigue. An exponential model was developed to predict the pull strength of the pulling tasks with embedded pauses. This model may be used to assess the developing of muscular fatigue for pulling tasks.

Self­-service for public transport payments: A business case for conversational artificial intelligence

<p>Although self-service (i.e. mobile top-ups) is at the heart of Snapper’s customer service offering, customers have a disjointed experience managing their public transport payment cards across a range of customer service touchpoints, including more traditional support channels such as helpdesks and in-person support centres. Customer feedback indicates that some Snapper users perceive the process of resolving support issues through these traditional support channels to be inconvenient and time-consuming. Activity through these traditional channels still forms a large proportion of Snapper’s customer service, despite Snapper’s ongoing investment in their self-service channels; including mobile applications, the website, the MySnapper desktop application, and kiosks. Just as Snapper innovated to meet customer demand for self-service through a mobile app (Snapper Services Ltd., 2017a), the evolution of conversational artificial intelligence (AI), or chatbot technology, presents an opportunity for Snapper to lead the way in meeting customer demand for a faster, more accessible way to resolve common support issues. The successful development of such a solution will further position Snapper as a market-leader in customer-centric innovation. In order to understand the commercial potential of such an automated customer service offering, the research aims to understand customer use and perceptions of Snapper’s support channels; to identify barriers to the adoption of self-service, and understand how these can be addressed; and to understand customer attitudes towards automated customer service. Using a mixed methods approach, research began with analysis of secondary data accessed from Snapper’s internal customer service reporting. Findings validated customer demand for additional self-service options, as well as the repetitive nature of Snapper’s customer service queries, indicating that these are ripe for automation. In-depth interviews were conducted with Snapper cardholders, giving further insight into how they select and interact with Snapper’s customer service channels. The avoidance of perceived effort was identified as a key theme when explaining how customers navigate service channels, supporting the role of “ease of use” in explaining customer adoption of self-service technologies (Davis, Bagozzi, & Warshaw, 1989). Types of perceived effort were identified as social, cognitive and logistical effort. These categories are proposed as an extension to the Technology Acceptance Model (Davis et al., 1989), giving additional insight into what constitutes “ease of use”. Following the in-depth interviews, market analysis and discussions with AI and chatbot service providers explored best practice in automated customer service, to understand the adoption of conversational AI technology in the New Zealand context, as well as how other companies have successfully implemented a chatbot product. The project report concludes with a stand-alone business case for applying conversational AI technology to Snapper’s customer service offering. The business case summarises the business model and delivery methodologies recommended for the project development (see Section 6.1), including LEAN startup methods. The market validation phase (Section 6.2) then addresses the strategic business case, assessing the case for change and incorporating key findings from the customer and market research conducted earlier in the research. Building on the opportunities identified in the PESTEL analysis, the product validation phase (Section 6.3) utilises a SWOT analysis, before providing clear recommendations around the required feature-set of the proposed solution, and a possible roadmap for implementing these features. Finally, the economic, financial and commercial cases are addressed; including a cost-benefit analysis of the proposed solution, a recommended development methodology, and high-level resources and requirements required for implementation. By validating that delivering such an enhanced self-service offering is commercially viable, the project aims to deliver a more delightful experience to Snapper users, driving better uptake of Snapper’s self-service channels.</p>

Self­-service for public transport payments: A business case for conversational artificial intelligence

<p>Although self-service (i.e. mobile top-ups) is at the heart of Snapper’s customer service offering, customers have a disjointed experience managing their public transport payment cards across a range of customer service touchpoints, including more traditional support channels such as helpdesks and in-person support centres. Customer feedback indicates that some Snapper users perceive the process of resolving support issues through these traditional support channels to be inconvenient and time-consuming. Activity through these traditional channels still forms a large proportion of Snapper’s customer service, despite Snapper’s ongoing investment in their self-service channels; including mobile applications, the website, the MySnapper desktop application, and kiosks. Just as Snapper innovated to meet customer demand for self-service through a mobile app (Snapper Services Ltd., 2017a), the evolution of conversational artificial intelligence (AI), or chatbot technology, presents an opportunity for Snapper to lead the way in meeting customer demand for a faster, more accessible way to resolve common support issues. The successful development of such a solution will further position Snapper as a market-leader in customer-centric innovation. In order to understand the commercial potential of such an automated customer service offering, the research aims to understand customer use and perceptions of Snapper’s support channels; to identify barriers to the adoption of self-service, and understand how these can be addressed; and to understand customer attitudes towards automated customer service. Using a mixed methods approach, research began with analysis of secondary data accessed from Snapper’s internal customer service reporting. Findings validated customer demand for additional self-service options, as well as the repetitive nature of Snapper’s customer service queries, indicating that these are ripe for automation. In-depth interviews were conducted with Snapper cardholders, giving further insight into how they select and interact with Snapper’s customer service channels. The avoidance of perceived effort was identified as a key theme when explaining how customers navigate service channels, supporting the role of “ease of use” in explaining customer adoption of self-service technologies (Davis, Bagozzi, & Warshaw, 1989). Types of perceived effort were identified as social, cognitive and logistical effort. These categories are proposed as an extension to the Technology Acceptance Model (Davis et al., 1989), giving additional insight into what constitutes “ease of use”. Following the in-depth interviews, market analysis and discussions with AI and chatbot service providers explored best practice in automated customer service, to understand the adoption of conversational AI technology in the New Zealand context, as well as how other companies have successfully implemented a chatbot product. The project report concludes with a stand-alone business case for applying conversational AI technology to Snapper’s customer service offering. The business case summarises the business model and delivery methodologies recommended for the project development (see Section 6.1), including LEAN startup methods. The market validation phase (Section 6.2) then addresses the strategic business case, assessing the case for change and incorporating key findings from the customer and market research conducted earlier in the research. Building on the opportunities identified in the PESTEL analysis, the product validation phase (Section 6.3) utilises a SWOT analysis, before providing clear recommendations around the required feature-set of the proposed solution, and a possible roadmap for implementing these features. Finally, the economic, financial and commercial cases are addressed; including a cost-benefit analysis of the proposed solution, a recommended development methodology, and high-level resources and requirements required for implementation. By validating that delivering such an enhanced self-service offering is commercially viable, the project aims to deliver a more delightful experience to Snapper users, driving better uptake of Snapper’s self-service channels.</p>

Effects of a Self-Regulated Training Program on the Repeated Power in Female College Handball Players: An Intervention Study

Several resistance training programs using conventional methodologies have been implemented with the purpose of improving the ability to perform power actions in handball, especially during the competitive season. In contrast, methodologies based on a contemporary perspective, which considers the human being as a self-regulating biological entity, and designed specifically for female college players, are scarce. The aim of this research was to investigate the effects of an eight-week resistance training program, in which the athletes were able to control the loads according to their self-perceived effort and rest on their repeated shuttle sprint and jump ability. The sample was composed of 16 female players of a handball team from the faculty of physics and mathematics sciences of a Chilean university. The RSSJA test was used to evaluate players’ conditions pre- and post-training program, and the self-perceived effort scale called OMNI-RES was used for the prediction and control of loads. Results indicated that, after the application of an eight-week resistance training program, significant improvements p ≤ 0.05 on the jump height (pre: 1836.4 W; average post: 2088.9 W) and running speed (average pre: 3.2 m/s; average post: 4.0 m/s) were obtained, as well as a significant reduction in the loss of power and speed between each set of the applied test.