Learning Platform Moderation: Research on Innovation of Online

Action Learning Instruction

Boren Gao and Jingxian Wang

Guizhou University of Commerce, Guizhou, 550014, China

Keywords: Online Action Learning, Mental Maturity, Personal Initiative, Platform Quality.

Abstract: Conforming to the trend of digital economy, business schools actively deepen the instruction reform and

promoted the "Internet+" Instruction mode. This study focuses on the influence mechanism of "online action

learning" instruction mode on college students' personal initiative, and uses the relevant concepts of infor-

mation system success model and mental maturity theory for reference, to study the influence relationship

among the four variables: learning platform quality, online action learning, college students' mental maturity

and college students' personal initiative. By randomly selecting 421 college students to conduct a survey, data

statistics and effect verification were also conducted, further analyzed the mechanism among the variables.

In a word, under the influence of students' mental maturity and learning platform quality, online action learn-

ing can have a positive impact on college students' personal initiative.

1 INTRODUCTION

For colleges, online instruction research focuses more

on the construction and effective use of information

platforms, while the adult characteristics of college

students are relatively less involved. The traditional

view is that only the behavior of students who are ed-

ucated in formal learning places like schools can be

called learning. In fact, college students are adults

like college lecturers, should be defined as a group

that can complete self-study with the help of ad-

vanced IT instruction models (Li, 2021). Especially

in the digital economy environment, adult learning

often takes place in informal places, such as online

communities or virtual communities (Wang, 2020).

This research believes that online action learning is

an important strategy to improve college students'

lifelong learning ability, and discusses the necessity

and applicability of online action learning instruction

mode from the theoretical level, demonstrates how

online action learning can promote college students'

personal initiative, and studies the mediation effect of

college students' mental maturity and the moderation

role of college learning platform quality. (Li, 2021;

Wang, 2020)

2 THE BASIC THEORY

2.1 The Platform Quality

The concept of platform quality can be traced back to

the theory of information system success model. This

model firstly studies the influence of information

quality, as shown in Figure 1, system quality and ser-

vice quality on users' usage intention and customer

satisfaction, and then further studies the effect of this

influence on net income, so as to find the path to op-

timize the information system (Cao, 2021).

Figure 1: Information System Success Model (Cao, 2021)

[Owner-draw]

The information provided in the online live teach-

ing platform is mostly resources related to teaching

and subject knowledge. Therefore, in the information

system of live teaching, it is more effective to define

Gao, B. and Wang, J.

Learning Platform Moderation: Research on Innovation of Online Action Learning Instruction.

DOI: 10.5220/0011911300003613

In Proceedings of the 2nd International Conference on New Media Development and Modernized Education (NMDME 2022), pages 321-327

ISBN: 978-989-758-630-9

 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

321

information quality as resource quality. Service qual-

ity refers to the user's evaluation of the service ob-

tained from the information system, including the re-

sponsiveness, accuracy, technical ability, etc. of the

service. Satisfaction is "the impact of users' actual use

of information systems". The intention to use refers

to the evaluation of users' actual behavior in using the

information system. As online live teaching is a man-

datory learning alternative to offline courses, it is

weak in the online live teaching platform, so this pa-

per does not consider it as a variable. The key link of

distance learning is knowledge sharing, which can be

seen as an information system use behavior. Net in-

come mainly refers to the benefit evaluation of users

using the information system (Cao, 2021; Bock G W,

2009). The online live teaching platform system em-

pirically analyzed in this study was closely related to

the learning ability of college students. The improve-

ment of the learning ability of users after using the

live teaching platform is called "net income". Moreo-

ver, based on the three factors of system quality, re-

source quality and service quality of the "information

system success model", combined with the character-

istics of the online live teaching platform, the plat-

form quality measurement factors were constructed,

and the 5 point Likert scale was used for measure-

ment.

2.2 Online Action Learning

The concept of action learning originates from man-

agement science. It was first proposed and developed

by the British scholar Revans. R in the middle of the

20th century. He applied this method to develop or-

ganizational business, improve and solve problems

encountered. It is a form of organizational learning.

The so-called online action learning, just as its name

implies, is the action learning carried out on the net-

work, which is the combination of online learning and

action learning (Li 2021, Wang 2020, Bock 2009,

Jiang 2021). With the in-depth development of infor-

mation technology in the "Internet+" era, the network

has become an important tool for human learning and

cognitive activities. Online learning based on the net-

work has been welcomed by teachers, lecturers and

education institutions for its immediacy, openness,

flexibility and other characteristics, and has been

widely used in various lecturer training projects (Li,

2021; Wang, 2020).

Online action learning is a learning method

emerging with the continuous combination of infor-

mation technology and adult learning. It is an online

and timely ability building process, and also a way for

learners to use online technology to implement spe-

cific action plans to solve practical work problems

and learn from them. In other words, online action

learning is action learning carried out through the In-

ternet, and the network is the carrier of its learning

activities. Teachers' online action learning not only

has the advantages of rapid updating and strong flex-

ibility of online learning knowledge, but also has the

characteristics of practical, reflective, cooperative

and cyclical action learning (Li 2021, Wang 2020,

Bock 2009, Jiang 2021). The lecturer professional de-

velopment project designed by the concept of online

action learning embodies lecturers' individual reflec-

tion and collective wisdom, and reflects the combina-

tion of individual progress and organizational devel-

opment. Based on the theory of action learning, this

research measures online action learning instruction

from four aspects: learning resource deployment,

group learning, questioning and reflection, and guid-

ance and catalysis. The 5 point Likert scale was used

for measurement.

2.3 Personal Initiative

Personal initiative is expected to be an effective be-

havior model for individuals and organizations to

cope with fierce competition, and is an important area

for organizations to focus on in the future (Gao 2018).

Based on the research of Free et al., (1994), this paper

believes that: The rapid development of science and

technology in the 21st century, the ever-changing dy-

namic environment, the new concept of organization,

and the new changes in the concept of work all make

the workers in it more and more need to adapt to and

tolerate this unstructured uncertainty. Therefore, the

concept of personal initiative, characterized by posi-

tive work attitude and active work behavior, has grad-

ually become an important concept of work perfor-

mance in the 21st century. Based on “the Personal In-

itiative Self statement Reporting Scale” compiled by

Free et al., (1997), this study emphasized four aspects

of college students' initiative behavior: initiative,

spontaneity, perform and endurance. The 5 point Lik-

ert scale was used for measurement. (Gao 2018, Frese

1994, Frese 1997)

2.4 Mental Maturity

Chris Argyris (1957), an American organizational be-

haviorist, believes that a person's maturity is actually

the degree of responsibility he is willing to take for

his own behavior, which includes two core elements,

namely, job maturity and mental maturity(Chris

1957). Mental maturity refers to the willingness and

NMDME 2022 - The International Conference on New Media Development and Modernized Education

322

motivation of an individual to make a certain behav-

ior. If an individual cannot consciously complete a

certain behavior, it means that the person's mental

maturity is low. On the contrary, it is higher (Zhang

2000). Generally speaking, it is a transformation pro-

cess from passive to active, from dependence to inde-

pendence, and from short-sighted to far-sighted.

Many domestic scholars have carried out in-depth re-

search on mental maturity, among which Zhang Li

believes that mental maturity belongs to the sociali-

zation process of individuals, that is, through the

training and accumulation of acquired social life, in-

dividuals will gradually form a process of stable psy-

chological quality that can meet the needs of social

life. The structure of mental maturity includes cogni-

tive maturity, consciousness maturity, emotional ma-

turity, self-consciousness maturity and personality

maturity (Zhang 2000, Chen 2009). With reference to

the research results of domestic and foreign experts

mentioned above, combined with the basic data of the

sample survey of undergraduate college students, this

study summarized the mental maturity of college stu-

dents into four levels: self cognition, psychological

endurance, independence and inclusiveness, The 5

point Likert scale was used for measurement.

3 RESEARCH HYPOTHESIS

3.1 Online Action Learning and

Personal Initiative

The impact of online action learning instruction on

students' personal initiative can be reflected in two as-

pects: (1) The school's behavior of building an online

course platform is a practice of action learning, which

provides students with the required teaching re-

sources and teaching environment. Taylor et al., pro-

posed that action learning can be based on the needs

of the organization itself to form a personalized social

support network, which plays a positive role in the

modular cross school integration and innovation of

resources. Specific to the instruction practice process,

online action learning can help them build a new

framework for knowledge output in SPOC teaching

design and environmental preparation (Li 2021,

Wang 2020, Bock 2009, Jiang 2021). (2) The instruc-

tion process of online action learning is the process of

developing students' learning habits. Lump-Kim

pointed out that action learning can create a more ef-

ficient, transparent and open knowledge system, rap-

idly improve the efficiency of organizational resource

management, and stimulate students' knowledge inte-

gration behavior on the basis of knowledge internali-

zation (Bock 2009, Jiang 2021, Gao 2018, Zhang

2010). Therefore, online action learning behavior can

gradually build a flexible curriculum system and

deeply mine learning data. Thus, the following as-

sumptions are proposed: H1. The application of

"online action learning" helps to improve the personal

initiative of college students in the daily learning pro-

cess.

3.2 Online Action Learning and Mental

Maturity

Online action learning instruction, through course al-

liances and course platforms, introduces heterogene-

ous resources between schools and within schools,

and deals with students' basic knowledge in advance.

It moves classroom learning from shallow to deep. It

is a cross-school resource management activity. It is

not only a simple combination of resources, but also

a instruction method that contains the dual character-

istics of exploratory innovation and utilization inno-

vation. In the process of cross-school resource inte-

gration, lecturers' learning and transformation of re-

sources will help to create new knowledge. Secondly,

online action learning can improve the novelty of

teaching materials. In the process of general and basic

curriculum teaching, teachers often fall into the di-

lemma of solidification of teaching thinking, and it is

difficult to innovate the teaching content only by in-

novating the teaching form. The online action learn-

ing classroom is different. As the main body of cross

domain integration of learning resources, students can

build new teaching content across industries and

fields through the existing online learning platform,

improve the novelty of teaching innovation, and im-

prove students' knowledge mastering speed and learn-

ing ability. The mental maturity of college students

can be summarized into four levels: self cognition,

psychological endurance, independence and inclu-

siveness. Finally, online action learning classroom

teaching can improve the construction speed of new

undergraduate courses. However, online action learn-

ing teaching can use the dual innovation ability mod-

ular reorganization of internal and external solutions

to help students quickly obtain the material and tech-

nical resources needed for learning, improve learning

speed, and then make a breakthrough in students' dual

learning ability (Li 2021; Wang 2020, Chris 1957,

Chen 2009, Zhang 2010). Therefore, this study pro-

poses the following assumptions: H2. online action

learning is conducive to the mental maturity and

healthy development of college students.

Learning Platform Moderation: Research on Innovation of Online Action Learning Instruction

323

3.3 Mental Maturity and Personal

Initiative

Personal initiative is not only the behavior of

knowledge acquirers to seek knowledge, but also the

behavior of knowledge providers to transfer and teach

knowledge. Therefore, in online teaching, lecturers

impart knowledge to students and improve their

learning ability, which is also a psychological inter-

action behavior. Through the openness and flow of

knowledge, students can realize the improvement of

psychological interaction and cognitive ability in the

systematic process of knowledge transfer, utilization

and feedback. Online live teaching class is similar to

offline class. It takes a small class group as a unit. In-

dividuals who like group work are more likely to in-

teract and share information frequently. This online

teaching with students' cooperative learning as the

core content is conducive to cultivating students' abil-

ities of autonomous learning, communication and ex-

pression (Gao 2018, Fres 1994, Chris 1957, Chen,

2009, Zhang 2010). It can be seen that the mental ma-

turity of college students is closely related to the ini-

tiative of individuals. In teaching reform, we should

respect the psychological characteristics of students

and create a good management environment in order

to truly realize the independent management of stu-

dents. Based on this, this study puts forward the fol-

lowing hypothesis: H3. the mental maturity of college

students is helpful to improve the personal initiative

of college students.

3.4 The Mediating Role of Mental

Maturity

The mental maturity of college students is an essential

factor for college instruction to gain competitive ad-

vantage. When mobilizing students to participate in

classroom teaching activities, the ability to handle,

understand and use information is as important as the

ability to deal with problems on the spot. Undoubt-

edly, effective mental sharing behavior can not only

help to form a strong learning atmosphere, but also

promote students' autonomous and spontaneous par-

ticipation behavior. When students' experience and

skills are shared in the classroom, it creates an oppor-

tunity for interactive learning, thus stimulating the

best learning practice, reducing the cost of ineffective

learning, helping to create and update knowledge at

the individual and team levels, and ultimately im-

proving the effectiveness of teaching. In addition, the

undergraduate colleges are implementing the national

education concept of educating all the students. While

paying attention to the improvement of students' skill

level, they pay more attention to the improvement of

students' humanistic quality and mental health (Chris

1957, Zhang 2000, Chen 2009, Zhang 2010). In par-

ticular, in the context of the digital economy, it is be-

lieved that through the efforts of schools and families,

the mental maturity of college students will gradually

improve, so that they have a strong tolerance and ad-

justment ability to maintain a relative psychological

balance, and promote the mental health and all-round

development of students. Thus, this study proposes

the following hypothesis: H4. the mental maturity of

college students plays a mediating role between

online action learning and personal initiative of col-

lege students.

3.5 The Moderation of Platform

Quality

Platform support refers to the platform interface de-

sign and platform function design that support learn-

ers to interact with deep knowledge, it enables learn-

ers to have a good user experience, meets the learners'

search and communication needs, and further makes

learners perceive fewer barriers to in-depth

knowledge interaction. When users feel that the plat-

form is very easy to use and do not need to waste too

much time to learn how to use it, they will think they

can use the platform well and improve their sense of

self-efficacy. And only when community members

feel it is very convenient to participate in the online

community, they are willing to communicate in the

community. It can be found that platform support af-

fects learners' views on the difficulty of deep

knowledge interaction (Cao 2021, Chris 1957, Zhang,

2010). Thus, this study proposes the following hy-

pothesis: H5. the quality of learning platform plays a

moderating role between action learning teaching and

students' mental maturity.

The stable and smooth quality of the platform di-

rectly promotes the development of learners' own

knowledge and ability through in-depth discussion

with other community members. In the online learn-

ing community, in order to acquire knowledge in the

process of communication and discussion with com-

munity members, those learners with stronger moti-

vation for knowledge often actively post. These learn-

ers will negotiate with others in the process of com-

munication and discussion until they reach an agree-

ment, verify the views again and transfer the new

views. The negotiation, examination and application

of views are all in the category of deep knowledge

interaction, so it can be found that learners with self-

development expectations will think that deep

knowledge interaction is valuable (Cao 2021, Gao

NMDME 2022 - The International Conference on New Media Development and Modernized Education

324

2018, Chris 1957, Zhang 2000, Zhang 2010). There-

fore, the following hypothesis is proposed: H6. the

quality of learning platform plays a moderating role

between college students' mental maturity and active

behavior.

4 VERRIFICATION OF

INTERNAL MECHANISM

4.1 Variable Preparation and Data

Processing

This survey controls the gender, age, and expected

earnings that may affect the relationship between

online action learning, mental maturity, and active be-

havior. Therefore, the potential variables are online

action learning, mental maturity, personal initiative

and platform quality, among which mental maturity

is the intermediary variable. Platform quality, gender,

age, and expected revenue are moderating variables,

as shown in Figure 2. In terms of data processing,

anonymous survey method was used to distribute 421

questionnaires to students in business colleges of Gui-

zhou Province, including 324 valid ones, with a re-

covery rate of 64.16%.

According to the 324 valid questionnaires col-

lected, the average age of students is 21, including

178 males and 146 females. SPSS18.0 statistical soft-

ware package and amos7.0 software were used to test

the reliability of the processed sample data. The re-

sults showed that Cronbach's a coefficients of all var-

iables were greater than the critical value of 0.7, and

the revised item population correlation coefficient

(CITC) was much greater than 0.35. Cronbach's a co-

efficient of all items after deleting the item is smaller

than the total a coefficient of the subscale, which

means that all items have good internal consistency

and should be retained. Each variable table passed

KMO sample measure and Bartlett sphere test, which

is suitable for further factor analysis.

Figure 2. The Final Structural Equation Model [Owner-

draw]

4.2 The Empirical Test

(1) Online action learning improves the test of per-

sonal initiative. According to the requirements of the

conceptual model, Mplus7.1 software is used to es-

tablish the initial structural equation model based on

the overall sample, import the data for fitting, and get

the fitting results of the initial model shown in Table

1: the chi square degree of freedom ratio of the initial

model fitting is 2.473, less than 3; The RMSEA value

is 0.071, less than 0.08; The values of CFI, GFI,

AGFI, NFI and NNFI are all higher than 0.9. The

overall fitting effect of the model is good, but the fit-

ting coefficient is only 0.014, which is not very sig-

nificant in the economic sense. H1 has not been effec-

tively verified. Online action learning cannot improve

the ability of personal initiative. Whether this conclu-

sion is scientific needs further verification.

(2) The mediating effect test of mental maturity.

From the analysis of the model, we can see that the

structural equation model excludes the influence

among many variables, such as the intermediary in-

fluence of mental maturity, such as the adjustment of

the quality of learning platform, and the adjustment

of age and gender. Therefore, the structural equation

model needs to be modified locally. In order to find

the optimal structural equation model graph, after re-

peated comparison and local verification, it is found

that the goodness of fit of the model is the best when

mental maturity is added as the intermediary variable

in the initial structural equation model graph.

(3) As shown in Figure 1, there are two significant

variables, namely, "mental maturity ← online action

learning"（β= 0.283, p<0.01), "active behavior ←

mental maturity"（β= 0.290, p<0.01）. The normal-

ized path coefficients in the figure are significantly

positive, indicating that the variables represented by

these paths have a significant positive impact rela-

tionship. Use Bootstrap program to test the signifi-

cance of mediation effect. The results in Table 1 show

that the 95% confidence interval of the influence path

does not contain zero, which means that there is a sig-

nificant intermediary effect between mental maturity,

online action learning and active behavior. It can be

seen from this that H1, H2, H3 and H4 have been

proved, that is, H2: online action learning signifi-

cantly improves mental maturity, H3: mental maturity

significantly improves personal initiative, and H4:

mental maturity has a mediating effect between

online action learning and students' personal initiative

has been verified. Based on the above three assump-

tions, H1: online action learning improves personal

initiative ability.

Learning Platform Moderation: Research on Innovation of Online Action Learning Instruction

325

(4) The moderating effect of learning platform

quality, age, gender and expected income on online

action learning, mental maturity and active behavior

interaction. Structural equation model was used to

test the moderating effects of learning platform qual-

ity, age, gender and expected income. According to

the median of learning platform quality, age, gender

and expected income, the students were divided into

four scales, and each scale was divided into two sub-

samples according to the score. The path coefficients

of the two subsamples were estimated by the struc-

tural equation model for each group, and the joint t-

test formula was used to test the moderating effect

(see Table 1).

There are significant differences between the path

coefficients of low-quality samples. Since the Z-value

of the joint t-test is all positive, it means that the qual-

ity of learning platform will significantly positively

regulate the relationship between online action learn-

ing, mental maturity and active behavior. From the

empirical results, it can be found that the high quality

of learning platform will promote the path coefficient

of “online action learning → mental maturity” and

“mental maturity → personal initiative”, so that the

path coefficient of online action learning → active be-

havior of high quality learning platform is signifi-

cantly higher than the coefficient of low quality learn-

ing platform.

There are significant differences between the path

coefficients of the male sample and the female sam-

ple. Since the Z-value of the joint t-test is all positive,

it means that gender significantly positively moder-

ates the relationship between online action learning,

mental maturity, and active behavior. From the em-

pirical results, it can be found that the path coeffi-

cients of online action learning → mental maturity

and mental maturity → personal initiative of boys are

significantly higher than those of girls, so that the per-

sonal initiative induced by online action learning of

boys is significantly better than that of girls.

Table 1. Test Results of Moderating Effect

Route

High

qual-

ity of

learn-

ing

plat-

form

Low

qual-

ity of

learn-

ing

plat-

form

Joint

T-

test

Male

stu-

dent

Fe-

male

stu-

dent Joint

T-

test

Senior

grade

Junior

grade

Joint

T-

test

High

thresh-

old of

ex-

pected

in-

come

Low

thresh-

old of

ex-

pected

in-

come

Joint

T-

test

Stand

ard

coef-

fi-

cient

Stand

ard

coef-

fi-

cient

Stand-

ard co-

effi-

cient

Stand-

ard co-

effi-

cient

Stand-

ard co-

effi-

cient

Stand-

ard co-

effi-

cient

Stand-

ard co-

effi-

cient

Stand-

ard co-

effi-

cient

Online

Action

Learn-

ing→Me

ntal Ma-

turit

0.351

0.120

3.15

0.317*

0.253*

0.64

0.303*

0.104*

6.41

0.197*

0.371*

5.00

Mental

Ma-

turity→

Personal

Initiative

0.330

0.153

4.03

0.286*

0.257*

0.01

0.293*

0.113*

5.93

0.114*

0.251*

3.98

Online

Action

Learn-

ing→Per

sonal In-

itiative

0.115

0.018

2.57

0.0906

0.0650

0.02

0.0117

0.0887

5.71

0.0931

0.0224

4.62

(Note: ** and * represent the significance level of 5% and 10%, respectively)

There are significant differences between the path

coefficients of the upper grade sample and the lower

grade sample. Since the Z-value of the joint t-test is

all positive, it means that age significantly positively

moderates the relationship between online action

learning, mental maturity, and active behavior. From

the empirical results, it can be found that the path co-

efficients of online action learning → mental maturity

and mental maturity → personal initiative of senior

students are significantly higher than those of junior

NMDME 2022 - The International Conference on New Media Development and Modernized Education

326

students, so that the personal initiative induced by

online action learning of senior students is signifi-

cantly better than that of junior students.

In the sample with low expected return standard,

there is a significant difference between the coeffi-

cients of each path and those of the sample with high

expected return standard. Since the Z values of the

joint T-test are all positive, this means that the ex-

pected return criterion will significantly and posi-

tively adjust the relationship between online action

learning, mental maturity and personal initiative.

From the empirical results, it can be found that a low

standard of expected return will promote the path co-

efficient of online action learning → mental maturity,

mental maturity → personal initiative, thus making

the path coefficient of online action learning → active

behavior with a low standard of expected return sig-

nificantly higher than that with a high standard of ex-

pected return.

5 CONCLUSION

This report is the result of the "2022 School-enter-

prise Integrated Education Project of the Ministry of

Education: Exploration and Research on the New

Business School Enterprise Integration Instruction

Mode in the Digital Economy" and the “Reform pro-

ject of the teaching content and curriculum system of

Guizhou's colleges: ecological civilization oriented

teaching reform of basic courses of economics and

management (No. 2022222)”. By analyzing the pro-

cess of online action learning instruction innovation

and empirically testing the influence relationship and

specific mechanism between the four variables of

learning platform quality, online action learning, stu-

dents' mental maturity and personal initiative, this

study believes that online action learning is a very ef-

fective instruction model to improve college students'

lifelong learning ability. The undergraduate business

school actively improves learning platform quality

and promotes the online action learning instruction

mode, which can promote the mental growth of col-

lege students and have a positive impact on the per-

sonal initiative of college students.

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