Effects of Proactive Personality and Social Centrality on Learning

Performance in SPOCs

Sannyuya Liu

1, 2

, Huanyou Chai

, Zhi Liu

, Niels Pinkwart

Xue Han

and Tianhui Hu

National Engineering Laboratory for Educational Big Data, Central China Normal University,

Luoyu Road 152, 430079 Wuhan, China

National Engineering Research Center for E-Learning, Central China Normal University,

Luoyu Road 152, 430079 Wuhan, China

Department of Computer Science, Humboldt University of Berlin, Unter den Linden 6, 10099 Berlin, Germany

Keywords: Social Centrality, Proactive Personality, Social Network Analysis, Learning Performance, SPOCs.

Abstract: Due to the adaptability and manageability in small-scale class teaching, Small Private Online Courses

(SPOCs) have become a highly important learning apparatus in higher education. However, what

psychological and social factors affect learning outcomes in SPOCs remains to be explored. This study aims

to investigate the effects of proactive personality and social centrality on learning performance in the

SPOCs context. On the one hand, we examine the independent effects of proactive personality and social

centrality respectively. On the other hand, the combined effect of them is studied to gain a comprehensive

understanding of the roles of psychological and social factors in students’ SPOCs learning process. Results

from correlation analyses indicate that proactive personality and social centralities are significantly

correlated with learning performance. Further regression and ANOVA analyses demonstrate the

applicability of the two models of indirection and interaction effects respectively.

1 INTRODUCTION

In recent years, due to the high student dropout rates

in Massive Open Online Courses (MOOCs), Small

Private Online Courses (SPOCs) have gained

increasing attention for their appropriateness and

manageability in small class teaching (Kaplan and

Haenlein, 2016). SPOCs are online courses that only

offer a limited number of places and therefore

necessitate some form of formal enrolment (Filius et

al., 2018). SPOCs are characterized by students’

intense intention to complete and considerably

meaningful interaction (Uijl et al. , 2017). However,

not all students favour and match this new form of

learning mode, as students are different in

psychological and social attributes (Liu et al., 2018).

Therefore, it is necessary to examine what factors

affect learning outcomes in SPOCs to advance their

adoption and

promotion.

Personality, one of the best known variables in

the psychological field, has been reported to be

closely related to students’ learning (e.g., Gatzka

and Hell, 2018). However, most of the existing

studies in this area are limited to the roles of Big

Five personality and traditional learning

environments (Keller and Karau, 2013). Besides,

students’ social positions in the network emerging

from interaction are also important for learning

process and success (Carceller et al., 2015; Kilduff

and Brass, 2010). Again, it remains to be unclear

whether the above relations apply for the SPOCs

context.

To address the research gap, this paper aims to

deal with the associations among proactive

personality, social centralities and learning

performance in SPOCs. Specifically, proactive

personality is chosen for its strong link with

cognitive or motivational factors in learning process,

such as self-efficacy (Brown et al., 2006; Major et

al., 2006), while social centralities are good

indicators of students’ positions in the learning

network (Carceller et al., 2015).

This paper is organized as follows. In Section 2,

we review the definition of proactive personality and

social centralities, and related research about their

relationships with learning performance in the

educational field with online learning for particular.

The design of this study is presented in Section 3.

Liu, S., Chai, H., Liu, Z., Pinkwart, N., Han, X. and Hu, T.

Effects of Proactive Personality and Social Centrality on Learning Performance in SPOCs.

DOI: 10.5220/0007756604810487

In Proceedings of the 11th International Conference on Computer Supported Education (CSEDU 2019), pages 481-487

ISBN: 978-989-758-367-4

481

Results are showed in Section 4. Section 5 concludes

findings in this study.

2 RELATED WORKS

Proactive personality, usually defined as “the

relatively stable tendency to effect environmental

change”, was proposed to explore the effect of

dispositional factors on individuals’ proactive

behaviour or proactivity (Batesman and Crant,

1993). Individuals with a high level of proactive

personality are more likely to take initiatives to

change the environment and persevere until meeting

expectations. In the educational context, proactive

personality was found to be linked with students’

feeling of self-efficacy and motivation to learn.

(Major et al., 2006; Prabhu et al., 2012), which were

good predictors of better learning outcomes.

Meanwhile, trait activation theory (Tett and Burnett,

2003) points out that environmental factors are

important for the expression of specific trait. As

SPOCs empower students with various opportunities

in terms of choosing when, where and what to learn

and interact (Uijl et al., 2017), learners in these

environments are free to exhibit their proactivity.

Thus, proactive personality may play an important

role in SPOCs learning.

Social centralities, including degree, closeness

and betweenness centrality, are often used to

determine an actor’s position in a network (Burt et

al., 2013). To be specific, degree centrality measures

the number of links incoming to an actor or outgoing

from an actor, closeness centrality is related to how

long would it take to propagate the information from

one actor to the rest, betweenness centrality gives an

idea about which actors connect groups of actors. In

the educational field, an actor often represents a

student. Given the importance of social attributes in

online learning, a plenty of literature has begun to

examine and verify the relationships between social

centralities and learning performance (e.g.,

Hernández-García et al., 2015; Liu et al., 2018). For

example, Liu et al. (2018) explored the relationship

between social centralities and outcomes and found

that learners in the central position tended to

perform better than their counter-parts.

Apart from the independently determinant roles

of social positions and individual personality on

learning performance, there is an increasing trend in

educational psychology with online learning in

particular that attempts to explore the combined

effect of these two factors. According to the

developmental contextualism (Vondracek and Fouad,

1994), proactive personality and social centralities

might exert their combined effect in the following

ways: 1) Indirect-effect model, namely, proactive

personality has a positive effect on social centralities,

which in turn lead to better performance; 2)

Interaction effect model, namely, the effects of

social centralities on performance will be different in

various levels of proactive personality, and vice

versa. However, while some studies on students’

online learning have suggested the need to examine

the combined effect of psychological and social

factors on learning outcomes (e.g.,

Hernández-García et al., 2015), empirical evidence

is still limited. Therefore, this study attempts to test

the aforementioned two models of indirection and

interaction effect in SPOCs context.

3 EMPIRICAL RESEARCH

3.1 Research Questions

Considering the increasing popularity of SPOCs in

higher education and the aforementioned gaps in the

previous literature, this study aims to address the

following two questions:

(1) Do proactive personality and social centralities

affect the learning performance of students in

SPOCs?

(2) What is the combined effect of proactive

personality and social centralities on students’

performance in SPOCs?

Based on previous findings (not confirmed for

the specific case of SPOCs yet), our hypotheses are

as follows:

(1) The greater the level of a student’s proactive

personality, the greater the students’ performance;

(2) The greater the level of a student’s social

centralities, the greater the students’ performance;

(3) Proactive personality has a positive effect on

students’ centrality, which in turn leads to a better

performance; namely, the indirection effect model;

(4) There is an interaction effect of proactive

personality and social centralities on students’

performance.

3.2 Research Objects and Dataset

We conducted our study in a SPOC course called

“Freshman Seminar” which was opened in the

autumn of 2016 in a Chinese university. The course

was designed to help every freshmen make a

personal plan of career development. The SPOC

platform allowed students to learn from the materials

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(e.g., video, PPT or text) uploaded by the assistant or

the instructors. An additional forum was used to

support students’ online discussions. A total of 204

freshmen and 8 instructors participated in this

course, and they generated 11607 posts altogether.

Three measures of social centrality (degree,

closeness and betweenness centrality) were

computed using Gephi 0.9.2 based on the interaction

of students.

To capture the level of proactive personality, a

Chinese version of proactive personality scale

revised by Shang and Gan (2009) was adopted to

survey the participants. Besides, students’

performance data was assessed by a rating of their

final work in a mark ranging from 1 (very bad) to 5

(very good). Unluckily, only 177 students’ data of

proactive personality and performance are available

due to incomplete answers or not handing in their

homework on time.

3.3 Data Analysis

In order to address the first two hypothesis,

correlation analyses using SPSS 22.0 were

performed to understand the relationship between

proactive personality, social centralities and

students’ performance. To validate the third

hypothesis, model 4 (mediation model) from the

SPSS macro PROCESS was performed to examine

the mediating role of social centralities in the

relationship between proactive personality and

learning performance. Finally, we followed the data

processing method of Lin et al. (2015) to test the last

hypothesis. In this method, students in this course

are divided into two groups based on the two

independent variables. In terms of proactive

personality, a student with an above-mean score is

placed in the high-level group of proactive

personality, while the remaining students are placed

in the low-level one. Also, the same method is

applied to social centrality. Then, a two-way

ANOVA and a subsequent test of simple main

effects are conducted to test the interaction effect of

proactive personality and social centralities on

learning performance.

4 RESEARCH RESULTS

4.1 Social Network Characteristics of

Students

Figure 1 displays the sociogram by degree by the

204 students and 8 teachers of the SPOC course. The

sizes of the nodes are used to identify students’

degree with larger nodes representing a more central

position. Colours are used to identify students’

performance and teachers: teachers are in blue,

students scoring 4 or above are in orange, students

scoring 3 or below are in green, the remaining

students are in yellow.

In terms of density, it was 0.101 with no isolated

student in the network. The average distance

between students was 1.92, indicating that most

people could be connected through only one student

apart. The network degree centralization was 97.21

with students’ network sizes ranging from 1 to 169.

Above 25% of the students had more than 48

partners in their individual network (namely, the

group that they directly communicated with), while

other 25% had less than 14 ones.

4.2 Preliminary Analysis

Figure 1: Overall sociogram.

Table 1 shows the descriptive statistics of proactive

personality, social centralities and performance.

Students rated their perceived level of proactive

personality above the midpoint (M = 3.97, SD =

0.48). Also, students’ performance data was above

the midpoint (M = 3.86, SD = 0.48).

Table 2 shows the correlations between proactive

personality, social centralities and performance.

Normal distribution of students’ performance and

proactive personality is confirmed by the analysis, but

that is not the case of the other measures. Therefore,

we conduct parametric correlation analysis (Pearson’s

r) and non-parametric analysis (Spearman’s rho).

Shaded cells in Pearson’s correlation section represent

variables where normal distribution could not be

assumed. From Table 2, there is a significant but low

Effects of Proactive Personality and Social Centrality on Learning Performance in SPOCs

483

Table 1: Mean and standard deviation of proactive personality, social centralities and performance.

Proactive

centrality

Degree

centrality

Closeness

centrality

Betweenness

centrality

performance

Mean

3.97

39.77

0.54

60.65

3.86

Standard

deviation

0.48

35.68

0.07

215.34

0.48

Table 2: Correlations among proactive personality, social centralities and performance.

Proactive personality

Performance

Spearman’s rho

Pearson’s r

Spearman’s rho

Pearson’s r

Degree centrality

0.19

0.23

0.20

0.26

Closeness centrality

-0.01

0.00

-0.07

-0.09

Betweenness

centrality

0.17

0.12

0.22

0.14

Proactive personality

0.53

p < 0.05

p < 0.01

Table 3: Regressions testing the indirection effect model.

Regression equation

Fitting index

Significance of coefficients

outcome

predictors

LLCI

ULCI

0.23

0.05

11.02

0.23

3.32

0.09

0.36

0.12

0.01

1.70

0.12

1.30

-0.06

0.29

0.55

0.30

28.04

0.14

2.34

0.02

0.26

0.50

***

6.71

0.35

0.64

0.53

0.29

28.56

0.08

2.06

0.01

0.15

0.52

***

7.10

0.38

0.66

DC = degree centrality; BC = betweenness centrality; PP = proactive personality; LP = learning performance;

LL = lower limit, CI = confidence interval, UL = upper limit.

Table 4: Two-way ANOVA testing the interaction effect model.

Source

F-value

PP × DC

2.01

11.03

PP × CC

0.42

2.15

PP × BC

0.62

3.23

Table 5: Tests of the simple main effects of proactive personality and degree centralities on performance.

Source

F-value

PP within DC (1)

0.98

5.34

PP within DC (2)

6.85

37.35

***

DC within PP (1)

0.27

1.23

DC within PP (2)

1.79

8.23

(1) = low-level group, (2) = high-level group

***

p < 0.001

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（a）

（b）

Figure 2: Interaction plots of the effects of proactive

personality and degree centrality on performance: (a) The

effect of proactive personality on performance at different

levels of degree centrality, (b) The effect of degree

centrality on performance at different levels of proactive

personality.

positive relation between degree, betweenness

centrality and performance or proactive personality.

However, this is not case for closeness centrality.

Besides, the correlation between proactive

personality and performance is significantly positive.

Therefore, the former two hypotheses are supported.

4.3 Regression Analysis and ANOVA

As closeness centrality is not significantly correlated

with proactive personality and performance, it is not

included in the test of the third hypothesis. Table 3

presents the results of the test of degree and

betweenness centrality as mediators in the association

between proactive personality and learning

performance; namely, the test of indirection effect

model. From table 3, proactive personality positively

predicts degree

centrality (β = 0.23, p < 0.01), which in turn

positively predicts learning performance (β= 0.14,

p < 0.05). However, proactive personality does not

predict betweenness centrality (β = 0.12, p > 0.05),

even though the effect of the latter variable on

learning performance is significant (β = 0.08, p <

0.05). Further, the overall test of indirection effect

indicates that the value is 0.01 with 95% confidence

interval ranging from -0.01 to 0.03. Therefore, the

third hypothesis is confirmed for degree centrality,

but not for betweenness centrality.

Table 4 presents the results of the two-way

ANOVA. The interaction effect of proactive

personality and degree centrality on learning

performance is significant, while that is not the case

for the interaction effects of the other two social

centralities and proactive personality. Then the

simple main effects of proactive personality and

degree centrality were separately tested, the results

can be seen in Table 5. Proactive personality

significantly predicts performance in both groups of

degree centrality, but the effect is higher for students

with high level of degree centrality. On the other

hand, degree centrality significantly predicts

performance only for students with high level of

proactive personality. The interaction plots can be

seen in Figure 2.

5 CONCLUSIONS

Our study leads us to some interesting results about

the relationships among proactive personality, social

centralities and students’ performance in SPOCs.

Specifically, we examined the bivariate correlation

among them and tested the effects of indirection and

interaction. The conclusions are as follows:

Proactive personality, as an individual attribute

beyond Big Five in the personality domain, is

significantly and positively correlated with learning

performance, while social centralities as social

attribute also have a significantly positive link with

it. According to the proactive motivational state

proposed by Parker et al. (2008), proactive

personality is beneficial for learners as its affordance

of activating higher level of self-efficacy and

motivation to learn. Besides, social network theory

(Krause et al., 2007) highlights that students in the

central position of learning network are more likely

to have access to valuable resources for learning.

Both of the indirection and interaction effect

model are validated. On the one hand, proactive

personality is an antecedent of social centrality,

3.2

3.4

3.6

3.8

4.2

4.4

Low PP High PP

Learning performance

Low DC High DC

3.2

3.4

3.6

3.8

4.2

4.4

Low DC High DC

Learning performance

Low PP High PP

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485

which in turn contributes to a better performance.

This finding challenges the traditional view of

structural determinism (a theoretical perspective

which highlights that social attributes are the major

determinant of human activities, and do not

recognize the effect of individual attributes on social

ones) and supports a decisive effect of individual

attributes on social ones. On the other hand, those

who possess both a high level of proactive

personality and social centrality can benefit most

from SPOCs learning. This finding can be

interpreted in the context of ecological systems

theory (Darling, 2007), which posits that individual

and social attributes interact to influence personal

development.

Based on the above research findings, we can

obtain some significant implications about SPOC

learning. Firstly, SPOCs forum should be well

designed to activate students’ proactive personality,

such as gamified design (Ding et al., 2018), or the

adoption of unstructured discussion forums (Salter

and Conneely, 2015). Secondly, social collaboration

or cooperation should be advocated in students’

learning in SPOCs. For example, Virtue (2017)

adopted small groups and moderators to enhance

students’ interaction in online writing courses.

Finally, instructors and educators are suggested to

build suitable learning environment for students in

accordance with their aptitudes.

ACKNOWLEDGEMENTS

This work was supported by the Research Funds

from National Natural Science Foundation of China,

National Key R&D Program of China, Hubei

Provincial Science and Technology Program of

China and Hubei Provincial Natural Science

Foundation of China.

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