Does CQA Online Platform Increase Academic Performance of

Secondary Students in Indonesia

Rahkman Ardi

, Adismara Putri Pradiri

, Handy Pratama

and Dimas Mukhlas Widiantoro

2 3

Faculty of Psychology, Universitas Airlangga

Brainly, Ul. Dluga 72, Krakow 31-146, Poland

Faculty of Economics and Business, Universitas Gadjah Mada

Keywords: Community Question and Answering, E-learning, Learning Style, Big Five Personality

Abstract: The effective use of a CQA platform supported by appropriate learning style and specific traits could boost

students’ academic performance. This research aims to investigate the difference in academic performance

between passive and active users of CQA, i.e. Brainly; and determine socio-psychological characteristics

distinguishing between those users. The participants completed questionnaires related to demographics and

psychology scale, i.e. Grasha-Reichmann Student Learning Style Scales (GRSLSS), Big Five Personality

Inventory, Academic Self-efficacy, and social interaction scale. Moreover, the students’ academic

performance was also measured by testing three subjects which are Indonesian (five questions), English

(five questions), and Mathematics (five questions) based on the education level of participants. The total

number of participants was 757 respondents consisting of 333 CQA active users and 424 CQA passive

users. The results of this research show that students having independent, contributive and competitive

learning styles tend to be more active in solving the problems of academic subjects. The users with high

self-efficacy along with a conscientious personality also tend to be active users. The active users also show

higher academic performance scores compared to the passive ones.

1 INTRODUCTION

The use of a Community Question and Answering

(CQA) online service aiming to support the students’

learning needs grows rapidly in Indonesia. Brainly

as a CQA platform and one of the biggest online

learning media in the world for high school students,

with one fifth of the total users being from Asia

(Erlangga, 2015). It has helped millions of high

school students in answering questions and doing

homework by conducting question and answer

interactions through online communities. The

Marketing Manager of Brainly stated that there are

100 million monthly users from the total of 35

countries, of which 24 million users are from

Indonesia (Ryza, 2018).

The rapid use of CQA to help students' learning

leads to pros and cons in the community. Bhaskoro

(2014) warned that Brainly could have two side

effects. On one side, this site can provide

opportunities for students to learn to understand a

problem in various subjects with other users. But on

the other side, the misuse problem is also possible as

seen in certain students who are too lazy to think and

just copy-paste for the assignments given by their

teacher. The misuse problem of this e-learning

platform has also been revealed by Barla, Kizlan,

and Vit’az (2016). They argue, “There will always

be a group of lazy students” who simply take the

solution given by others without any effort to

participate or interpret it.

Based on those assumptions, this study aims to

establish how the socio-psychological characteristics

of users who are actively involved in CQA activities

differ from those who only want to get quick

answers through the platform. These socio-

psychological characteristics are reflected in daily

learning styles, personality profiles and general

academic self-efficacy. Online interaction patterns

and academic performance of CQA active users are

also observed as learning process indicators and

effective use of an e-learning platform.

Alfonseca, et al (2006) revealed that learning

style influences how students select strategy and

collaborate with others. This fact refers to Kolb’s

(1999) findings, which explain that the selection of a

particular learning style has an impact on the choice

of effective learning strategies based on group

Ardi, R., Pradiri, A., Pratama, H. and Widiantoro, D.

Does CQA Online Platform Increase Academic Performance of Secondary Students in Indonesia?.

DOI: 10.5220/0008587201990206

In Proceedings of the 3rd International Conference on Psychology in Health, Educational, Social, and Organizational Settings (ICP-HESOS 2018) - Improving Mental Health and Harmony in

Global Community, pages 199-206

ISBN: 978-989-758-435-0

199

dynamics. However, the study by Alfonseca, et al.

(2006) has still been based on learning style used by

the Felder and Silverman model. This model

categorizes learning style into five elements, which

are sensing-intuitive (how to perceive information),

visual-verbal (how to present information),

inductive-deductive (how to organize information),

active-reflective (how to process information) and

sequential-global (how to understand information)

(Felder and Silverman 1988). Meanwhile Kolb

(1999) bases learning style on how someone

perceives and processes information.

In this study, the definition of learning style

refers to the student’s interaction with teachers and

peers in their daily lives (Grasha, 1996). This

definition is more related to social perspective on

learning style rather than on how students perceive

information (auditory, visual, kinesthetic and

tactile). This learning style, based on social

interaction, consists of six indicators which are 1)

independent which means individuals who tend to

learn alone; 2) dependent which means individuals

who depend on the teacher; 3) collaborative which

means individuals who engage in working with

others; 4) competitive which means individuals who

compete with others; 5) participative which means

individuals who learn by joining in an activity; 6)

avoidant which means individuals who avoid and are

not interested in learning (Grasha, 1996).

The interaction in CQA is based on group

dynamic activity and relationships among its

members. Therefore, preferences and learning

strategies in e-learning are also assumed to be

representations and reflections of the daily learning

interactions in the classroom between students,

teachers and peers. In this case we assume that CQA

users actively involved in answering questions also

represent a learning pattern in the classroom that

tends to be independent, collaborative, competitive

or participatory.

The study conducted by Chen and Caropreso

(2004) indicated that personality influences online

discussion in which students with higher

extraversion, agreeableness and openness tend to be

more involved in online collaborative learning.

Furthermore, Zhang (2003) revealed that

neuroticism predicts a superficial learning approach

rather than an in-depth learning approach. Students

with high neuroticism avoid risk in activities

involving trial-and-error experiences. It can be

assumed that students with high neuroticism tend to

engage as those who like to raise questions rather

than being those who like to answer the questions.

Conscientiousness and openness to experience also

become the most influential predictors in in-depth

learning strategy and achieving approach (Zhang,

2003). Thus, it can be concluded that students with a

tendency to four high personality traits

(conscientiousness, openness, extraversion and

agreeableness) will tend to engage in collaborative

and in-depth strategies. One of those strategies can

be manifested in answering/solving other users'

questions in a CQA.

In addition, Bates and Khasawneh (2007) have

stated that self-efficacy is a predictor in the use of e-

learning indicated in outcome expectations, mastery

perceptions and time spent per week in accessing

online learning technologies. Although the study

only describes self-efficacy in online learning, it

should be applicable in general academic self-

efficacy. Consequently, academic self-efficacy

driven by mastery perceptions of academic lessons is

assumed to be able to influence user activity on the

online learning platform, especially in active

participation relationships to answer community

questions.

The relationship between academic performance

and the type of users (both active and passive) is

also investigated in this study. Davies and Graff

(2005) stated that the quality and dynamics of

interaction could be the important factor of academic

performance. Cho, et al. (2007) pointed out that a

collaborative learning environment on social

networks has a significant effect on academic

performance. A study conducted by Agudo-

Peregrina, et al. (2014) revealed a significant

relationship between the type of interaction and

academic performance in e-learning. More

specifically, an experiment conducted by Nestojko,

et al. (2014) showed that students who are asked to

learn with instruction to teach others achieve better

academic performance than those who only learn to

prepare for the exam. Therefore, in this study we

assume that users who interact actively through

answering activities or solving the problems of

academic subjects achieve better academic

performance.

In addition, level of satisfaction and interaction

forms shown among fellow active CQA users were

also investigated in this study. The forms of

interaction consist of collaboration, conflict,

competition and accommodation. Exploring the type

of interaction between active and passive users is

believed to be useful for CQA designers to create

features that support social and hard skills

improvement through collaboration and competition,

as well as conflict resolution through

ICP-HESOS 2018 - International Conference on Psychology in Health, Educational, Social, and Organizational Settings

200

accommodation so that online learning can work

more effectively.

Overall CQA users are divided into two

categories: 1) passive users, those who browse the

Brainly content and those who use Brainly only to

ask questions; 2) active users, those involved in the

activities of answering questions/solving problems.

Based on those categorizations, this study aims to

answer the following hypotheses (H) and research

questions (RQ):

H1. Personality profiles (i.e. extraversion,

agreeableness, conscientiousness, neuroticism and

openness to experience) affect user type. Individuals

with extraversion, agreeableness, conscientiousness

and openness tend to be active users. In addition,

individuals with high neuroticism tend to be passive

users.

H2. Active users show higher academic self-

efficacy than passive users.

H3. Active users achieve better academic

performance than passive users.

RQ1. Are there any differences in learning styles

(independent, dependent, competitive, collaborative,

participative, avoidant) between active and passive

users?

RQ2. How do active users interact with each

other, especially in the form of interactions,

satisfaction levels and the desire to continue the

interaction.

2 METHODS

The participants were high school students who

became the visitors and Brainly users aged 12 to 18.

They varied from grade 1 junior high school to grade

3 senior high school. They were then divided into 2

groups which were active users (users involved in

question and answer activities) and passive users

(users who only seek answers and ask questions).

During the period from June to October 2017, we

obtained 757 respondents consisting of 333 active

users involved in answering questions and 424

passive users and visitors ranged from grade 1 junior

high school to grade 3 senior high school. However,

there were 27 respondents who needed to be

excluded because they were doing academic

performance tests outside their grade so that there

were 730 respondents to be analyzed. The gender

proportions in this research were 349 women and

381 men. 44% of participants were active on the

Internet for more than four hours per day, while 49%

used the Internet for one to four hours per day, and

only 6% were active on the Internet for less than an

hour.

Research sampling was done by sending

invitations to all users of Brainly Indonesia either

through an account or through a pop up on the

Brainly.co.id web page. The participant involvement

in this study is voluntary.

Participants completed demographic related

questionnaires (age, gender, internet access at school

and home, the amount of time spent online per day

and the amount of time to access Brainly).

Furthermore, this study also measured students'

academic performance scores on specific subjects

based on their grade levels. The tested subjects were

Indonesian (five questions), English (five questions)

and Mathematics (five questions). Those subjects

were selected, as they became three main subjects in

the evaluation of national examinations held by the

Ministry of Education and Culture.

Participants completed the questionnaires of the

socio-psychological dimensions i.e. Grasha-

Reichmann Student Learning Style Scales

(GRSLSS), academic self-efficacy, Big Five

Personality Inventory and social interaction scale.

The translation of GRSLSS, academic self-efficacy

scale, and Big Five Personality Inventory from

English to Indonesian was done by using forward

translation. GRSLSS was created by Grasha and

Reichmann (Grasha, 1996). This scale is used to

explore students’ learning styles based on interaction

with teachers and peers. This scale consists of six

categorizations which are 1) independent (α = 0.61);

2) dependent (α = 0.67); 3) collaborative (α = 0.84);

4) competitive (α = 0.75); 5) participative (α = 0.81);

6) avoidant (α = 0.65). In each category the used

learning styles are 3 items only.

The next psychological scale is the short version

of the Big Five Personality Inventory adapted from

Rammstedt and John (2007). This scale measures

the personality types on extraversion, agreeableness,

conscientiousness, neuroticism and openness to

experience. In each personality type there are two

questions.

Academic self-efficacy is modified from the

general self-efficacy scale created by Schwarzer and

Jerusalem (1995). One example of this item is “I can

remain calm when facing academic difficulties

because I can rely on my coping abilities.” This

scale consists of 5 items with Cronbach alpha of

0.85.

The social interaction scale is constructed for the

purpose of this study. This scale consists of six

dimensions with each having three items which are

1) desire to interact (“I do not mind to continue my

Does CQA Online Platform Increase Academic Performance of Secondary Students in Indonesia?

201

Table 1: The Analysis Results of Big Five Personality, Self-efficacy, and Learning Styles.

Dimension

Mean (SD)

of Active

Users

Active

users

Mean of

Passive

Users

passive

users

Cohens’d

Extraversion

728

5.16 (2.18)

314

5.36 (2.00)

416

1.30

0.19

0.09

Agreeableness

728

5.81 (1.45)

314

5.63 (1.54)

416

-1.60

0.10

0.12

Conscientiousness

629.70

5.80 (1.63)

314

5.29 (1.49)

416

-4.29

0.00***

0.32

Neuroticism

728

4.91 (1.58)

314

4.90 (1.54)

416

-0.08

0.93

0.01

Openness to

Experience

728

5.52 (1.22)

314

5.59 (1.15)

416

0.72

0.47

0.05

Self-efficacy

728

5.02 (1.12)

314

4.83 (1.13)

416

-2.28

0.02

0.17

Independent

709.76

5.71 (0.85)

314

5.50 (0.96)

416

-3.06

0.00**

0.23

Dependent

728

4.88 (1.22)

314

4.70 (1.21)

416

-1.87

0.06

0.14

Participative

728

5.41 (1.20)

314

5.13 (1.25)

416

-3.03

0.00**

0.23

Competitive

728

5.86 (1.09)

314

5.26 (1.17)

416

-2.77

0.00**

0.53

Collaborative

728

5.29 (1.22)

314

5.23 (1.30)

416

-0.61

0.54

0.05

Avoidant

728

3.74 (1.28)

314

4.32 (1.36)

416

5.83

0.00

0.44

*p < 0.05 ** p < 0.01 *** p < 0.001

friendships with other Brainly users”, α = 0.50); 2)

satisfaction to interact (“I enjoy interacting with

others at Brainly”, α = 0.72); 3) teamwork (“I do not

mind working on a team to solve learning problems

with other Brainly users”, α = 0.44); 4) competition

(“I answer the difficult question to be the best user

of Brainly”, α = 0.78); 5) conflict (“I have no doubt

arguing and defending my statements or answers in

Brainly forums if I am criticized by other users”, α =

0.77); 6) accommodation (“I bridge some of the

responses that spark the debate among the Brainly

answerers”, α = 0.76).

3 RESULT

Table 1 presents the statistical analysis result of

independent t-test among participant categories in

Big Five Personality Scale, learning style, and self-

efficacy. That table answers H1, H2 and RQ1.

Hypothesis 3 (H3) is presented in Table 2 with the

statistical analysis result on each level of education.

Table 3 presents the statistical analysis result of

social interaction scale which answers RQ2.

Based on the analysis of independent t-test, the

active users showed a conscientiousness score

higher than the passive users (t (639.70) = -4.29; p <

.001, d = 0.32). However, the level of extraversion (t

(728) = -1.30; d = 0.09), agreeableness (t (728) = -

1.60; d = 0.12) and openness to experience (t (728) =

0.72; d = 0.05) were not different significantly

between both user groups. The level of neuroticism

was also not different significantly (t (728) = -0.08;

d = 0.01).

Consequently, H1 was confirmed partially in

which the conscientious personality dimension of

active users was higher than the passive ones.

Meanwhile, the other four personality

dimensions,which are extraversion, agreeableness,

openness to experience and neuroticism were not

different significantly between both user groups.

H2 was confirmed through the result showing

that academic self-efficacy of the active users tends

to be higher than the passive ones (t (728) = 0.72; p

< .05, d = 0.17).

There was a significant difference between the

active and passive users on academic performance (t

(703) = -4.16; p < .001, d = 0.32) which explains

that the active users showed higher

ICP-HESOS 2018 - International Conference on Psychology in Health, Educational, Social, and Organizational Settings

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Table 2: The Analysis Result of Academic Performance at each level of education.

Grade

Mean (SD) of

Active Users

Active

Users

Mean of

Passive Users

Passive

Users

Cohens’d

Total Score

703

8.48 (2.74)

308

7.58 (2.87)

397

-4.16

0.00***

0.32

1 junior high

school

7.90 (3.16)

8.20 (3.57)

0.30

0.76

0.09

2 junior high

school

10.19 (2.68)

8.60 (2.88)

-2.37

0.02*

0.57

3 junior high

school

8.54 (2.59)

7.17 (2.98)

-2.42

0.01*

0.49

1 senior high

school

113

9.02 (2.95)

7.73 (3.36)

-2.13

0.03*

0.40

2 senior high

school

152

8.00 (2.29)

8.23 (2.33)

0.61

0.54

0.09

3 senior high

school

215

7.87 (2.60)

6.77 (2.56)

131

-3.07

0.00**

0.42

*p < 0.05 **p < 0.01 ***p < 0.001

scores (M = 8.48, SD = 2.74) than the passive ones

(M = 7.58, SD = 2.87). Specifically, the score

between those users differed significantly on grade 2

junior high school, grade 3 junior high school, grade

1 senior high school, and grade 3 senior high school

(see Table 2). The insignificant difference could be

seen in grade 1 junior high school and grade 2 senior

high school (see Table 2). However, generally, this

analysis indicated that H3 was confirmed.

The analysis result of RQ1 shows that there was

a significant difference in learning styles between

the active users (N=314) and the passive ones

(N=416) on independent (t (709.763) = -3.06; p <

.01, d = 0.23), competitive (t (728) = -2.77; p < .01,

d = 0.53), participative (t (728) = -3.03; p < .01, d =

0.23) and avoidant (t (728) = 5.83; p < .001, d =

0.44) strategies, but there was no significant

difference on dependent strategy (t (728) = -1.87; d

= 0.14) and collaborative strategy (t (728) = -0.61; d

= 0.05).

The analysis of RQ2 showed that there was a

significant difference in all interaction patterns

between Brainly active and passive users. The score

of collaboration (t (715) = -6.73; p < .001, d = 0.51),

competition (t (714) = -5.75; p < .001, d = 0.44),

conflict (t (713) = -2.84; p < .01, d = 0.22) and

accommodation (t (711) = -2.71; p < .01, d = 0.19)

was higher and owned by the active users (see Table

3). The higher satisfaction level of interaction was

also shown by the active users

Table 3: The Analysis of Social Interaction Scale on Active and Passive Users.

Dimension

Mean (SD)

of Active

Users

Active

Users

Mean of

Passive Users

Passive

Users

Cohens’d

Interaction

satisfaction

718

5.79 (1.04)

313

5.35 (1.07)

407

-5.51

0.00**

0.41

Desire to continue

interaction

718

5.31 (1.09)

313

4.69 (1.02)

407

-7.88

0.00**

0.59

Competition

714

4.75 (1.24)

310

4.16 (1.44)

406

-5.75

0.00**

0.44

Conflict

713

4.53 (1.40)

310

4.21 (1.50)

405

-2.84

0.00*

0.22

Collaboration

715

5.43 (1.01)

310

4.92 (0.98)

407

-6.73

0.00**

0.51

Accommodation

711

5.02 (1.16)

309

4.78 (1.24)

404

-2.71

0.00*

0.19

*p < 0.01 **p < 0.001

Does CQA Online Platform Increase Academic Performance of Secondary Students in Indonesia?

203

(t (718) = -5.51; p < .001, d = 0.41) compared to the

passive ones (see Table 3). The Brainly active users

were also more interested in continuing further

interaction (t (718) = -7.88; p < .001, d = 0.59) than

the passive ones (see Table 3).

4 DISCUSSION

As stated in the first and second hypotheses, the

psychological variables indicate that someone who

has a level of self-efficacy and a high level of

conscientiousness will tend to become an active

user. Self-efficacy refers to a person's level of

confidence regarding his or her ability to perform

and to complete academic tasks. Conscientious

personality is a personality dimension, which

indicates the focus and control to achieve a specific

purpose. Users who have a low level of those

psychological variables tend to become passive

users/visitors. Instead, this fact indicates that people

who become active users in Brainly tend to have

confidence in solving the problems of academic

subjects and have an orientation and control to

achieve certain purposes. This statement is in line

with the results of the study by Bates and

Khasawneh (2007), which reveals that activities

indicating academic mastery of e-learning correlates

positively to self-efficacy. Zhang (2003) also stated

that the conscientious personality type is a

purposeful and strong-willed individual. Referring to

this fact, it is not surprising that individuals with

high personality conscientiousness tend to be more

active in answering problems and providing

solutions in CQA.

However, in this study openness to experience,

neuroticism, agreeableness and extraversion

dimensions do not show significant differences

between the active and passive users. In contrast to

Zhang's research (2003) stating that openness to

experience positively influences deep learning

activities and deep strategy, in this study learning

activity is limited and specific to answering

questions. In answering the questions, a person can

apply inventive and creative ways and be open-

minded (high openness to experience) or a person

can be cautious, dogmatic, and also closed-minded

(low openness to experience).

The insignificant relationship to the dimensions

of neuroticism, as found in this study, might be

explained by considering the accuracy level of

responses/answers given by users who also require

moderation from the Brainly moderator. This fact

shows that the problem-solving activity in CQA

done by the users is not always accurate. This

accuracy indicates that individuals actively involved

could have high self-control and confidence (low

neuroticism) or even be reactive (low emotional

control) in answering.

Furthermore, the non-significant relationship

between the type of active and passive users on the

agreeableness dimension is thought to be due to the

Brainly reward given to active users. The reward

means that activities of answering questions are not

only driven by altruism but also transactional.

Individuals with high agreeableness, who base their

attitude on altruism, sympathy and teamwork will

tend to find difficulties being involved in learning

activities that are achievement oriented (Zhang,

2003). The motive of a person when answering a

question is not only based on altruism but also the

transactional motive in the hope of getting the

reward as promised by Brainly.

Extraversion personality types also cannot be

distinguished significantly only by looking at which

users tend to be active and which tend to be passive.

Users with high extraversion type - who are often

regarded as individuals who are attention seeking

and domineering or low extraversion types - who

tend to shy away from social relationships have

opportunity to be both active or passive users. The

nature of CQA online, which is relatively

anonymous can cause a person, regardless of their

extraversion level, to engage intensely in the activity

of asking or answering questions.

This study also confirms the hypothesis that

users who are actively involved in solving the

problem of academic subjects at CQA will tend to

achieve better academic performance when

compared to passive users. This confirms an

experiment conducted by Nestojko, et al. (2014)

stating that students who study with the goal of

teaching it to others will achieve better academic

performance than those who are just learning to

prepare for the exam. They will have better and

complete memory when they are asked to teach it to

others. This study finds there is a significant

difference in learning scores between active and

passive users at various levels of education,

especially for students in grade 2 junior high school,

grade 3 junior high school, grade 1 senior high

school, and grade 3 senior high school. In those

levels of education, the average score of students

who become active users is higher when compared

to those who become passive users. The difference

between active and passive users is not significant

enough for grade 1 junior high school and grade 2

senior high school. For grade 1 junior high school

ICP-HESOS 2018 - International Conference on Psychology in Health, Educational, Social, and Organizational Settings

204

that result might be obtained due to active users who

join in this research being too few (22 users). While

in grade 3 senior high school, the proportion

between active (N = 57) and passive (N = 97) users

who joined was not balanced.

In the first research question (RQ1), it can be

concluded that the learning styles which are

independent, competitive, participative and avoidant

affect the type of users in Brainly. Students with

independent, participative and competitive learning

styles tend to be the type of user who is active in

answering questions in Brainly. Independent

learning style is indicated by the independence to

consider academic problems more deeply.

Competitive learning style is a learning model driven

by the competition to get better results. Participative

learning style could be seen from the level of student

participation in the activities conducted in the

classroom. Avoidant learning style is characterized

by students who do not show interest in the

classroom learning activities. The passive users tend

to perform avoidant learning style when they are in

class.

Interestingly, collaborative learning style does

not show a significant difference between passive

and active users. This result may be because of the

reward system in CQA. Although, the CQA platform

could stimulate collaborative action between users,

rewarding every individual answer to the question

may lead the users to be not only driven by the

pleasure of sharing or collaborating with others, but

certain action of users might be driven by the

transactional motive of competition to obtain certain

personal reward or recognition.

The result of this study also indicates significant

differences in interaction forms between active and

passive users. The active users understand the

importance of mutual interaction between users.

These active users do not only work together to give

the best answer, but they can also engage in conflict

situations, competition and accommodating action to

solve the conflict. Understanding the principle of

reciprocity and collaborative action taken by the

active users is not surprising if found in active users

because this platform is based on mutual exchange

among users so that they can help each other in

solving the problems of academic subjects.

However, competitive relationships in answering

other users' questions are also felt by active users.

They are competing to achieve higher status

regarding their membership in Brainly. This fact

exists since the users' activeness in answering

questions will obtain reward from Brainly whether it

is status promotion or rewards in the form of

souvenirs and certificates. Conflict in the form of

mutual refutation and debating answers in Brainly is

also common among the active users. However,

accommodating interactions are also prominent.

Brainly becomes a medium in which they can also

mediate discussions, compromise and revise answers

that are already shared.

Brainly active users indicate their satisfaction in

using the platform as a medium for interaction and

sharing among users, rather than those who are

passive users/visitors. They do not object to

continuing their interactions outside of CQA

activities either face-to-face or online through other

social media.

The results of this study generally show that

CQA users such as those on Brainly are able to

obtain the benefits if they are actively involved in

answering questions. These users obtain high scores

in academic performance compared to passive users.

This indicates that exercise and courage in solving

the problems of academic subjects in Brainly can

improve students' academic performance. It also

does not close the possibility for teachers to use

Brainly as a means of training for their students to

answer questions.

Another benefit from using Brainly is the

increased peer interaction among users. This social

interaction is not only a mutual reciprocal, but also a

relationship that requires soft-skill, especially with

the ability to manage conflict and accommodate any

discussions that occur within the platform.

The limitation of this study is related to the

degree of generalization. The sampling was based on

voluntarily participation instead of random

sampling. The proportion of the sample number of

passive and active users in grade 1 junior high

school was too small and grade 2 senior high school

was not balanced.

Although the study was funded by Brainly so

that it raises the presumption of possibility of

conflict of interest, the potential bias has been

prevented using scientific methods and admitting the

limitation of the study. It is realized from the

beginning that any e-learning platform including

Brainly can be used positively to increase academic

understanding related to their academic subjects, but

the misuse problem is potentially present for those

who only look for instant answers without any effort

to understand the academic subjects. Therefore,

future studies need to explore deeply the traits and

the motives in passive and active users, especially

those associated with self-regulation and instant

gratification motives in completing academic task.

In addition, the in-depth study, whether the behavior

Does CQA Online Platform Increase Academic Performance of Secondary Students in Indonesia?

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and academic achievement in the classroom are

directly proportional to the activity undertaken in

CQA, needs to be explored. It could be by

comparing their CQA activities with GPA.

Identification of these facts could also be useful for

CQA designers to provide features that can prompt

students to learn optimally.

ACKNOWLEDGEMENTS

This research was financially supported by Brainly.

We are thankful to Erik Choi for his valuable advice

on this study.

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