Lijia Lin

Animated agents and learning: Does the type of verbal feedback they provide matter?

The current study was conducted to investigate the effects of an animated agents presence and different types of feedback on learning, motivation and cognitive load in a multimedia-learning environment designed to teach science content. Participants were 135 college students randomly assigned to one of four experimental conditions formed by a 2 x 2 factorial design with agent presence as one factor (agent vs. no-agent) and type of verbal feedback it provided as the other factor (simple feedback vs. elaborate feedback). Results revealed that participants who learned with the animated agent that delivered elaborate feedback had significantly higher scores on a learning measure compared to participants who learned with an agent that provided simple feedback. The results are interpreted from both social agency and cognitive load theoretical perspectives.

Effects of visual cues and self-explanation prompts: empirical evidence in a multimedia environment

The purpose of this study was to investigate the impacts of visual cues and different types of self-explanation prompts on learning, cognitive load, and intrinsic motivation in an interactive multimedia environment that was designed to deliver a computer-based lesson about the human cardiovascular system. A total of 126 college students were randomly assigned in equal numbers (N = 21) to one of the six conditions in a 2 × 3 factorial design with visual cueing (cueing vs. no cueing) and type of self-explanation prompts (prediction prompts vs. reflection prompts vs. no prompts) as the between-subjects factors. The results revealed that (a) participants presented with cued animations had significantly higher learning outcome scores than their peers who viewed uncued animations, and (b) cognitive load and intrinsic motivation had different impacts on learning outcomes due to the moderation effect of cueing. The results suggest that the cues may not only enhance learning, but also indirectly impact learning, cognitive load, and intrinsic motivation.

Using a computer game to teach school-aged children about asthma

ABSTRACT The purpose of this study was to determine whether playing Quest for the Code™, a computer game designed to teach children about asthma, would help healthy children acquire knowledge about and attitudes towards asthma and whether the beneficial effects would be maintained over time. The sample consisted of 155 children from four middle schools who were randomly assigned to play Quest for the Code™ or a game about nutrition serving as the control condition. Data were collected on knowledge and attitude pre-intervention, post-intervention, and at follow-up four weeks later. The results revealed that children who played Quest for the Code™ were more knowledgeable and had more positive attitudes than their peers in the control condition. And these benefits were maintained on follow-up tests. Our findings indicate the effectiveness and potential of using Quest for the Code™ as a tool for asthma education in a classroom setting.

The Impact of Teaching Presence on Online Engagement Behaviors

Guided by the Interactive-Constructive-Active-Passive framework, the purpose of the study was to investigate whether teaching presence would impact online learners’ passive, active, constructive, and interactive engagement behaviors. A total of 218 middle-school English teachers participated in an online professional development course. Quantitative data were collected from an online survey and the log files of the online course website. The results of the regression analysis revealed that, by controlling for the potential effects of the demographic variables, learners’ perceived teaching presence had a positive impact on their constructive and interactive engagement behaviors but not on their passive or active engagement behaviors. In light of these findings, implications, limitations, and future directions are discussed.

Affect Recognition in Learning Scenarios: Matching Facial- and BCI-Based Values

The ability of a learning system to infer a students affects has become highly relevant to be able to adjust its pedagogical strategies. Several methods have been used to infer affects. One of the most recognized for its reliability is face-based affect recognition. Another emerging one involves the use of brain-computer interfaces. In this paper we compare those strategies and explore if, to a great extent, it is possible to infer the values of one source from the other source.