Dataset Information

Impact of personality traits on learners' navigational behavior patterns in an online course: a lag sequential analysis approach.

ABSTRACT: Personality is considered as the internal factor that defines a person's behavior. Therefore, providing adaptive features and personalized support in online learning by considering learners' personalities can improve their learning experiences and outcomes. In this context, several research studies have investigated the impact of personality differences in online learning. However, little is known about how personality differences affect learners' behavior while learning. To fill this gap, this study applies a lag sequential analysis (LSA) approach to understand learners' navigational behavior patterns in an online three-months course of 65 learners based on their personalities. In this context, the five factor model (FFM) model was used to identify learners' personalities. The findings revealed that learners with different personalities use different strategies to learn and navigate within the course. For instance, learners high in extraversion tend to be extrinsically motivated. They therefore significantly navigated between viewing the course module and their personal achievements. The findings of this study can contribute to the adaptive learning field by providing insights about which personalization features can help learners with different personalities. The findings can also contribute to the field of automatic modeling of personality by providing information about differences in navigational behavior based on learners' personalities.

SUBMITTER: Tlili A

PROVIDER: S-EPMC10245556 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Impact of personality traits on learners' navigational behavior patterns in an online course: a lag sequential analysis approach.

Tlili Ahmed A Sun Tianyue T Denden Mouna M Kinshuk Graf Sabine S Fei Cheng C Wang Huanhuan H

Frontiers in psychology 20230523

Personality is considered as the internal factor that defines a person's behavior. Therefore, providing adaptive features and personalized support in online learning by considering learners' personalities can improve their learning experiences and outcomes. In this context, several research studies have investigated the impact of personality differences in online learning. However, little is known about how personality differences affect learners' behavior while learning. To fill this gap, this ...[more]

PMID: 37292512

Similar Datasets

Project description:Improving standards of living have resulted in an increased focus on health and image management. In a context where the quality of healthcare information is unguaranteed, the adoption behavior intention of online health information varies greatly. Hence, it is essential to take effective measures to guide community users to obtain high-quality information on demand. From the perspective of personality traits, the present study analyzed the influencing factors and mechanisms of adoption behavior intention of healthcare information in online healthcare communities as well as the moderating effects of social support. A quantitative analysis of 380 respondents revealed positive associations between five personality dimensions and the adoption behavior intention of healthcare information-extraversion, agreeableness, conscientiousness, neuroticism, and openness. The study also determined that health concerns and health-related self-efficacy played a mediating role across various degrees between the conscientiousness and adoption behavior intention of healthcare information. As an important contextual factor influencing health outcomes, social support is common in online healthcare communities. The study examined the effect of the interaction between inner traits and social support on adoption behavior intention. Perceived self-esteem support strengthened the indirect effect of conscientiousness on adoption behavior intention mediated by health concerns and health-related self-efficacy. Additionally, the impact of high neuroticism interacted with low levels of perceived self-esteem support on adoption behavior intention was significant. Likewise, emotional supportive information did not help in facilitating the adoption behavior intention in terms of all five personality traits and negatively influence the adoption behavior intention for individuals high in neuroticism and agreeableness. The possible explanation for the results was discussed with the intention of understanding the psychological mechanisms which guide adoption behavior intention.

Project description:BACKGROUND:Personality traits have been associated with a series of dysfunctional behaviors, ranging from violence to drug abuse and other risky behaviors. However, few studies have investigated motorcycle riders' personality traits, and no research using the psychobiological model of personality was found. Thus, we investigated the association between temperament and character traits and the occurrence of Motorcycle Accidents (MAs). METHODS:This cross-sectional study was conducted with a randomly selected of 153 Brazilian motorcycle riders (116 male and 37 female) with a mean age of 31.8randomly selected from the driver's license register, between 2015 and 2018. A sociodemographic questionnaire and the Temperament and Character Inventory (TCI) were used. RESULTS:Of the 153 participants, 146 (95.4%) reported having been involved in previous accidents, with the main causes as follows: "other drivers' careless behavior" (34.9%); "personal disrespect of traffic rules" (18.5%) and "personal careless behavior" (20.6%). Motorcyclists exhibited higher scores for the temperament factors of novelty seeking and persistence and lower scores for harm avoidance and reward dependence in comparison to the Brazilian population). Considering the reason for motorcycle use, the group of riders that used their motorcycles for work exhibited more temperament factors associated with risk behaviors than those who did not. It was observed that 68.9% of them had low Harm Avoidance (HA) factor scores, whereas 72.1% had high Novelty Seeking (NS) factor scores. DISCUSSION:The present study highlighted the influences of different personality traits on behaviors, decision-making and risk attitudes that can be potentially harmful to an individual and others. The results provided evidence that a lack of knowledge and experience in riding a motorcycle or any other vehicle, combined with personality traits, contribute to the adoption of risky behaviors that may act as triggers for most causes of Motorcycle Accidents.

Dataset Information

Impact of personality traits on learners' navigational behavior patterns in an online course: a lag sequential analysis approach.

Publications

Impact of personality traits on learners' navigational behavior patterns in an online course: a lag sequential analysis approach.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets