Online social adaptation of first-year students and their academic performance

Krasilnikov, Alexander; Smirnova, Anna

doi:10.1016/j.compedu.2017.05.012

Cited by 26 publications

(26 citation statements)

References 37 publications

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“…Paul, Baker, and Cochran (2012) found that devoting time to social networking sites has a negative impact on academic performance. According to other studies, this negative impact mainly occurs when social networking sites are used in the classroom because multitasking diminishes performance (Bellur, Nowaka, & Hullb, 2015;Wood et al, 2012), and when the students involved are in their first year of university (Junco, 2015;Krasilnikov & Smirnova, 2017;Liu, Chen, & Tai, 2017). It seems that students who use social media spend less time studying, with an adverse effect on outcomes (Kirschner & Karpinski, 2010).…”

Section: Literature Reviewmentioning

confidence: 98%

“…One such variable currently considered of particular importance is social relations (Bond, Chykina, & Jones, 2017). It has been demonstrated that the social connections undergraduate students establish in their first few months of university life can exert an influence on their academic performance (Krasilnikov & Smirnova, 2017) due to the signal importance for these students of building a network of contacts, which can in turn help improve academic performance (Pascarella & Terenzini, 2005).…”

Section: Introductionmentioning

confidence: 99%

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The Impact of Social Media Participation on Academic Performance in Undergraduate and Postgraduate Students

Santoveña-Casal

2019

IRRODL

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The main objective of this study was to analyse the influence of social media participation on academic performance. The sample consisted of 1960 students taking one of two courses at undergraduate or postgraduate level, respectively (Faculty of Education, National Distance Education University, Spain), of whom 411 students carried out an activity based on social media participation. We used a mixed quantitative (descriptive analysis and ANOVA) and qualitative (content analysis) design. Our results showed that the students who participated in a social media-based activity presented better academic performance than those who did not carry out any activity or who took part in a more traditional learning activity. We conclude that regardless of educational level, social media participation exerts a positive influence on performance. Consequently, it is important to consider the variable of social networking site use because this can partially explain academic performance. We also found that the networks generated during the course did not constitute stable communities of practice. Our main recommendation is that three stages of instruction should be considered when designing a course based on social media participation: beginners, intermediate, and professional.

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Section: Literature Reviewmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

The Impact of Social Media Participation on Academic Performance in Undergraduate and Postgraduate Students

Santoveña-Casal

2019

IRRODL

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“…Social relationships are a significant part of the university experience of undergraduate students. The social media has become common among teenagers, most of the relationships maintained in real life are also translated online [3].…”

Section: Introductionmentioning

confidence: 99%

Relief-F and Budget Tree Random Forest Based Feature Selection for Student Academic Performance Prediction

Deepika*¹,

Sathyanarayana²

2019

IJIES

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Now-a-days, research in educational mining focuses on modelling student's performance. Many universities include large volumes of data related to student's details, performance, management details, educational process, and etc. Moreover, most of the data remains unused because inability of the university administration to handle it, also huge volumes of data are difficult to perform. In this paper, hybrid Feature Selection (FS) method namely Relief-F and Budget Tree-Random Forest (RFBT-RF) is proposed for selecting active features to reduce high dimensionality and handle uncertainty of data. The proposed feature selection method selects only relevant features instead of selecting redundant and irrelevant features for the classifiers. Also, RFBT-RF method is applied on multiple classifiers like Decision Tree (DT), Naive Bayes (NB) and Support Vector Machine (SVM) and K-Nearest Neighbour (KNN) for predicting the Student Academic Performance (SAP). RFBT-RF method was applied on three databases such as UCI (maths), UCI (Portuguese) and Collected dataset. Results showed that, RFBT-RF algorithm achieved 6.85% of improved SAP accuracy compare to the existing Logistic Regression (LR) model.

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“…Various aspects of cyber socialization of young people in recent years have been widely studied in psychology, sociology and other sciences. At the same time, in addition to the term "cyber socialization" (e.g., see [1, p. 123]), other related concepts are also widely used:  cyber socializing [2], socializing in cyberspace [3];  online socialization [4], online socializing [5] and online social adaptation [6];…”

Section: Introductionmentioning

confidence: 99%

Cyber Socialization of Russian Youth: Risks of Professional Self-determination

Lenkov¹,

Rubtsova²

2019

Proceedings of the II International Scientific-Practical Conference "Psychology of Extreme Professions" (ISPCPEP 2019)

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This study examined the role of cyber socialization in various kinds of professional choices (field, profession, job, university). The sample consisted of 605 employed individuals, 181 males and 424 females, who graduated from university in the period from 2003 to 2017. We used the «Utrecht work engagement scale (UWES)» and a biographical questionnaire to assess the correctness and stability of professional choice, the importance and effectiveness of cyber technologies in it. The results of ANOVA showed that the graduation time factor increased the role of cyber socialization in professional self-determination but the efficiency of the appropriate application of cyber technologies remains insufficient in many aspects. For example, the cyber technologies importance factor increases the correctness of the university choice but reduces work absorption, a professional motivation indicator; in the group with high cyber technologies importance, the time factor increases the correctness of the job choice but reduces the correctness and stability of professional choice. Thus, cyber socialization gives certain advantages in matters of professional self-determination but does not overcome emerging negative trends which results in new risks associated with the fact that the widespread use of cyber technologies does not always help to make a correct and sustainable professional choice.

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Online social adaptation of first-year students and their academic performance

Cited by 26 publications

References 37 publications

The Impact of Social Media Participation on Academic Performance in Undergraduate and Postgraduate Students

The Impact of Social Media Participation on Academic Performance in Undergraduate and Postgraduate Students

Relief-F and Budget Tree Random Forest Based Feature Selection for Student Academic Performance Prediction

Cyber Socialization of Russian Youth: Risks of Professional Self-determination

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