Corrigendum: The impact of pedagogical agents' gender on academic learning: a systematic review.

[This corrects the article DOI: 10.3389/frai.2022.862997.].

Multi-LEX: A database of multi-word frequencies for French and English.

Written word frequency is a key variable used in many psycholinguistic studies and is central in explaining visual word recognition. Indeed, methodological advances on single-word frequency estimates have helped to uncover novel language-related cognitive processes, fostering new ideas and studies. In an attempt to support and promote research on a related emerging topic, visual multi-word recognition, we extracted from the exhaustive Google Ngram datasets a selection of millions of multi-word sequences and computed their associated frequency estimate. Such sequences are presented with part-of-speech information for each individual word. An online behavioral investigation making use of the French 4-gram lexicon in a grammatical decision task was carried out. The results show an item-level frequency effect of word sequences. Moreover, the proposed datasets were found useful during the stimulus selection phase, allowing more precise control of the multi-word characteristics.

The Impact of Pedagogical Agents' Gender on Academic Learning: A Systematic Review.

Virtual learning environments often use virtual characters to facilitate and improve the learning process. These characters, known as pedagogical agents, can take on different roles, such as tutors or companions. Research has highlighted the importance of various characteristics of virtual agents, including their voice or non-verbal behaviors. Little attention has been paid to the gender-specific design of pedagogical agents, although gender has an important influence on the educational process. In this article, we perform an extensive review of the literature regarding the impact of the gender of pedagogical agents on academic outcomes. Based on a detailed review of 59 articles, we analyze the influence of pedagogical agents' gender on students' academic self-evaluations and achievements to answer the following questions: (1) Do students perceive virtual agents differently depending on their own gender and the gender of the agent? (2) Does the gender of pedagogical agents influence students' academic performance and self-evaluations? (3) Are there tasks or academic situations to which a male virtual agent is better suited than a female virtual agent, and vice versa, according to empirical evidence? (4) How do a virtual agent's pedagogical roles impact these results? (5) How do a virtual agent's appearance and interactive capacities impact these results? (6) Are androgynous virtual agents a potential solution to combatting gender stereotypes? This review provides important insight to researchers on how to approach gender when designing pedagogical agents in virtual learning environments.