The positivity principle: do positive instructors improve learning from video lectures?

Abstract

The positivity principle states that people learn better from instructors who display positive emotions rather than negative emotions. In two experiments, students viewed a short video lecture on a statistics topic in which an instructor stood next to a series of slides as she lectured and then they took either an immediate test (Experiment 1) or a delayed test (Experiment 2). In a between-subjects design, students saw an instructor who used her voice, body movement, gesture, facial expression, and eye gaze to display one of four emotions while lecturing: happy (positive/active), content (positive/passive), frustrated (negative/active), or bored (negative/passive). First, learners were able to recognize the emotional tone of the instructor in an instructional video lecture, particularly by more strongly rating a positive instructor as displaying positive emotions and a negative instructor as displaying negative emotions (in Experiments 1 and 2). Second, concerning building a social connection during learning, learners rated a positive instructor as more likely to facilitate learning, more credible, and more engaging than a negative instructor (in Experiments 1 and 2). Third, concerning cognitive engagement during learning, learners reported paying more attention during learning for a positive instructor than a negative instructor (in Experiments 1 and 2). Finally, concerning learning outcome, learners who had a positive instructor scored higher than learners who had a negative instructor on a delayed posttest (Experiment 2) but not an immediate posttest (Experiment 1). Overall, there is evidence for the positivity principle and the cognitive-affective model of e-learning from which it is derived.

I am Alexa, your virtual tutor!: The effects of Amazon Alexa’s text-to-speech voice enthusiasm in a multimedia learning environment

“…Noteworthy, this study's finding could have been attributed to the immediate posttest, which might not have effectively detected voice enthusiasm effects on learning outcomes (Wang et al, 2022). A delayed posttest may be more sensitive for discerning voice effects on learning performance concerning deep learning (Lawson et al, 2021b) and long-term knowledge acquisition (Davis et al, 2019).…”

“…Whereas, for the learners subjected to the high mental load conditions, the enthusiastic human voice increased extraneous cognitive load while decreasing germane cognitive load. Other studies found that while human voices with positive emotional tones such as enthusiasm and happiness in a multimedia learning environment enhanced learning performance, perceived difficulty was not impacted by the voices (Lawson et al, 2021b;Liew et al, 2017Liew et al, , 2020Wang et al, 2022).…”

“…Lawson and her colleagues further derived the Positivity Principle from the Cognitive Affective Model of E-learning; that is, learners can recognize a pedagogical agent's or human instructor's expressed positive and active emotion tones, which elevates the instructor's persona ratings and learning performance in a multimedia learning environment (Lawson & Mayer, 2021;Lawson et al, 2021c). Empirical studies have demonstrated that learners inferred the instructor's emotional tones comprising valence (positive/negative) and activity (active/passive) (Lawson & Mayer, 2021;Lawson et al, 2021a, b, c), and that positive and active expressed emotional tones tended to enhance the instructor's persona ratings (Lawson et al, 2021a, b), effort (Lawson et al, 2021a, b), and learning performance on a delayed posttest (Lawson et al, 2021b). Horovitz and Mayer (2021) proposed a slightly different version of the Cognitive Affective Model of E-learning, postulating the following links: (1) learners recognize the instructor's affective states based on their expressed emotional tones, (2) learners experience the same affective states following the instructor's affective states, (3) the adopted affective states of learners influence their motivational states, and (4) learners' motivational states affect learning performance (see Fig.…”

“…Additionally, reproducing text-to-speech voice enthusiasm with a longer-duration multimedia learning material can clarify whether extended exposure to a text-to-speech enthusiastic voice can cause habituation (Beege et al, 2020) or adverse effects due to learners perceiving the synthetic emotion as annoying, uncanny, or fake (Liew et al, 2016). Future studies in this research stream should consider utilizing a delayed posttest, which is more sensitive than an immediate posttest for measuring voice effects on deep learning and long-term knowledge acquisition (Davis et al, 2019;Horovitz & Mayer, 2021;Lawson et al, 2021b).…”

Instructors’ expressive nonverbal behavior hinders learning when learners’ prior knowledge is low

“…It was consistent with a previous study. Lawson et al (2021b) proved that positive instructors promoted the enjoyment of the lesson. This can be explained from both emotional contagion and emotional response theory.…”