The Role of Individual Learner Differences and Success in the Online Learning Environments

Colorado, Jozenia; Howell, Dusti

doi:10.4018/978-1-60566-830-7.ch006

Cited by 16 publications

(12 citation statements)

References 15 publications

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“…According to Pintrich, Smith, Garcia and McKeachie (1993), learning strategies consist of three categories and nine subordinates. Colorado and Howell (2009) summarized a detailed description of each component as follows:…”

Section: Learning Strategiesmentioning

confidence: 99%

How people learn in an asynchronous online learning environment: The relationships between graduate students’ learning strategies and learning satisfaction | Comment apprennent les gens dans un environnement d’apprentissage en ligne asynchrone

Choi¹

2016

CJLT / RCAT

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The purpose of this study was to examine the relationships between learners’ learning strategies and learning satisfaction in an asynchronous online learning environment, in an attempt to shed some light on how people learn in an online learning environment. One hundred and sixteen graduate students who were taking online learning courses participated in this study. The result revealed that ‘metacognitive strategy’ and ‘time and study environment’ had positive correlations with learners’ satisfaction, while ‘help seeking’ had a negative correlation. The findings of a multiple regression analysis showed that ‘metacognitive strategy’ and ‘peer learning’ led to learners’ satisfaction in an online learning environment. The findings of this study contribute to a better understanding of how successful learning occurs in an online learning environment, and provide recommendations on designing an effective online learning. L’objet de cette étude était d’examiner les relations entre les stratégies d’apprentissage des apprenants et la satisfaction liée à l’apprentissage dans un environnement asynchrone d’apprentissage en ligne, dans le but de faire la lumière sur les façons dont les gens apprennent dans un environnement d’apprentissage en ligne. Cent seize étudiants aux cycles supérieurs qui suivaient des cours en ligne ont pris part à cette étude. Les résultats ont révélé que la « stratégie métacognitive » et « le moment et l’environnement pour l’étude » avaient des corrélations positives avec la satisfaction des apprenants, alors que « demander de l’aide » avait une corrélation négative. Les conclusions d’une analyse de régression multiple ont démontré que la « stratégie métacognitive » et « l’apprentissage entre pairs » avaient des corrélations positives avec la satisfaction des apprenants dans un environnement d’apprentissage en ligne. Les conclusions de cette étude contribuent à une meilleure compréhension des façons dont un apprentissage réussi se produit dans un environnement d’apprentissage en ligne et fournissent des recommandations sur la conception d’un apprentissage en ligne efficace.

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Section: Learning Strategiesmentioning

confidence: 99%

How people learn in an asynchronous online learning environment: The relationships between graduate students’ learning strategies and learning satisfaction | Comment apprennent les gens dans un environnement d’apprentissage en ligne asynchrone

Choi¹

2016

CJLT / RCAT

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“…Younger students also struggled more than mature students to adapt to online environments (Xu and Jaggars, 2013). Several factors are shown to contribute to this view, as a result of age increase, for instance, elaboration, critical thinking and metacognitive self-regulation (Colorado and Eberle, 2010). Montgomery and Groat (1998) infer those mature students having life experiences are more inclined to be independent learners.…”

Section: Multi-group Analysismentioning

confidence: 99%

Learning self-efficacies influence on e-servicescapes: rethinking post-pandemic pedagogy

D’Souza

Kappelides

Sithole

et al. 2023

JSM

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Purpose The post-pandemic recognises changes are required; universities need to rethink their e-servicescapes strategies by offering different approaches to enhance students’ learning. This study aims to draw on learning self-efficacy trajectories and propose a conceptual model for exploring the predictive validity of satisfaction. In addition, it explores the mediating role of e-servicescapes and the moderating relationship effect of mature and younger students. Design/methodology/approach Learning self-efficacies is incorporated into the design of the model in an attempt to understand student cognition. The influences of e-servicescape on adopting online preferences and satisfaction are also examined. The model was empirically validated by surveying 266 respondents. Structural equation modelling and multi-group analysis were used to analyse the data. Findings The results of this study show learning self-efficacies has no significant influence on satisfaction. Yet, they showed a significant influence on e-servicescapes. E-servicescapes positively influenced satisfaction and preference for adopting online learning. E-servicescapes also had a mediating effect between self-efficacy to complete a course and satisfaction, as well as self-efficacy to interact with instructors and satisfaction. It had a negative suppressed effect on social interaction. Originality/value The research makes the following contributions. Firstly, the conceptualised model identifies an association between learning self-efficacies and e-servicescapes, suggesting universities as service providers can maximise the value offerings of their customer assets. Secondly, e-servicescapes demonstrate a full mediating effect between self-efficacies and satisfaction, indicating that if universities are to compete successfully in dynamic markets, they should co-create value in their e-servicescapes domain to increase satisfaction. Thirdly, the study recognises the need for a hybrid system of both face-to-face and online delivery because the multi-group analysis shows mature age preference for online learning is required to make this transformation successful.

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“…It is important to know demographic characteristics (age, gender, attended classes, grades awarded and academic achievement) for understanding engagement of students in learning environment and relationship between IA and FoMO. When the literature is examined, studies are found to address relationship between engagement in online learning environment and demographic characteristics such as age, gender and ethnicity (Colorado and Eberle, 2010;Hamby, 2015;Ke and Xie, 2009;Schneider and Germann, 1999;Teoh et al, 2013;Yoo and Huang, 2013). When the results of the relevant studies are examined, it is seen that different findings are obtained in the matter of effect of age and gender on engagement in learning environment.…”

Section: Students' Demographic Characteristics As Predictor Of Se Fom...mentioning

confidence: 99%

“…Studies reveal that there is a positive relationship between academic achievement of students with engagement in online learning environments (Colorado and Eberle, 2010;Alt, 2015;Lei et al, 2018;Zhang et al, 2018). In this case, demographic characteristics which affect academic achievement may also affect engagement of students in learning environments.…”

Section: Students' Demographic Characteristics As Predictor Of Se Fom...mentioning

confidence: 99%

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Examining the predictors of university students' engagement, fear of missing out and Internet addiction in online environments

Avcı

Kula

2022

ITP

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PurposeRecently, online learning and online environments have become even more important. Students' engagement, fear of missing out and Internet addiction are seen as interrelated components that affect students' online teaching and learning process. In this context, university students' engagement, fear of missing out and Internet addiction in online environments, the relationship among them and students' demographic characteristics, online environment usage status and Internet usage profiles as their predictors are examined in this study.Design/methodology/approachThis is a relational study and is carried out with 179 university students. Personal information form, student's engagement, fear of missing out and Internet addiction scales were used as data collection tools. Descriptive statistics, t-test, one-way ANOVA, correlation, hierarchical linear multiple regression analysis are used for the analysis.FindingsAccording to the results, variables related to students' demographic characteristics, online environment usage status and Internet usage profiles together significantly predict the students' engagement, fear of missing out and Internet addiction in online environments. When students think positively about taking courses online, their engagement increases accordingly and their fear of missing out levels decrease. Increase in student's academic achievement leads to decline in Internet addiction.Practical implicationsIn practice, examining the related variables about students in terms of engagement to the learning environment, fear of missing out and Internet addiction could bring a new perspective to studies on problematic use of the Internet and technology such as nomophobia and digital distraction. The results of this study reveal how and which components to be focused on for increasing the university students' engagement, reducing Internet addiction and fear of missing out in online learning environments.Originality/valueThe findings of this study provide a versatile perspective with the variables of student participation, fear of missing out, Internet addiction and their predictors in online learning environments, which are becoming widespread and increasingly important today and shed light on future researches.

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The Role of Individual Learner Differences and Success in the Online Learning Environments

Cited by 16 publications

References 15 publications

How people learn in an asynchronous online learning environment: The relationships between graduate students’ learning strategies and learning satisfaction | Comment apprennent les gens dans un environnement d’apprentissage en ligne asynchrone

How people learn in an asynchronous online learning environment: The relationships between graduate students’ learning strategies and learning satisfaction | Comment apprennent les gens dans un environnement d’apprentissage en ligne asynchrone

Learning self-efficacies influence on e-servicescapes: rethinking post-pandemic pedagogy

Examining the predictors of university students' engagement, fear of missing out and Internet addiction in online environments

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