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http://ijhe.sciedupress.com International Journal of Higher Education Vol. 9, No. 5; 2020
Published by Sciedu Press 346 ISSN 1927-6044 E-ISSN 1927-6052
The Role of Smart Working in Mediating Participatory Altruistic
Leadership, Competence, Quality knowledge in Learning Performance
of Lecturers in Higher Education
Sri Handayani1, DYP Sugiharto1, Joko Sutarto1 & Kardoyo1
1Doctoral Program of Education Management Departement, Universitas Negeri Semarang, Semarang, Indonesia
Correspondence: Sri Handayani, 1Doctoral Program of Education Management Departement, Universitas Negeri
Semarang, Semarang, Indonesia.
Received: July 9, 2020 Accepted: August 13, 2020 Online Published: August 18, 2020
doi:10.5430/ijhe.v9n5p346 URL: https://doi.org/10.5430/ijhe.v9n5p346
Abstract
This study aims to explore indicate that lecturer learning performance is an important factor for lecturers in the Civil
Engineering Education Study Program. Participatory altruistic leadership styles, competence, quality knowledge,
smart working are very important to be measured to explain their effects on learning performance. If the lecturer has
high competence and quality knowledge and is supported by appropriate leadership, it will have an impact on smart
working, which in the end will achieve learning performance. This research was conducted of lecturers of civil
engineering education throughout Indonesia and a sample of 76 peoples. The research method was conducted with
quantitative and data analysis using structural equation modeling (SEM). Regression coefficient result that
relationship between competence with smart working, participatory altruistic with smart working and quality of
knowledge with smart working were 0.80, 0.86 and 0.81. Regression coefficient result that relationship between
smart woking with learning performance, participatory altruistic with learning performance, quality knowledge with
smart working and competence with smart working were 0.99, 0.91, 0.88, and 0.88.
Keywords: competence, learning performance, participatory altruistic, quality knowledge, smart working
1. Introduction
1.1 Problem Identification
Lecturer learning performance is influenced by the ability of individuals to manage their abilities. The ability of each
lecturer depends on the level of quality knowledge possessed, professionalism, sense of social in communicating and
dealing with colleagues and students (Babalola, 2016). Lecturer learning performance is related to the quality of
individuals in higher education. Learning performance will affect the quality of a study program in a university.
Lecturer learning performance is an achievement generated in accordance with the passion and expertise of the
lecturer (Nasir et al., 2018). Productive behavior is the employees who deliberately hinder the fulfillment of
organizational goals that contribute negatively to the organization (Hussain et al., 2016). Pedagogy and other
lecturers' competencies influence learning performance. Stakeholders, students and the community will be motivated
by lecturers who have good competence. So that lecturer competence becomes an important factor in learning
performance for the development of quality human resources. The orientation of the lecturer and the intelligent work
of the lecturer in planning, making formulations, implementing good plans that have been prepared and then willing
to conduct evaluations in carrying out their performance affect the quality of the study program. Expertise, skills in
self-management and interacting with the surrounding environment become added value for lecturers in learning
performance (Sugiharto et al., 2018). Lecturer learning performance can take place well if supported by leadership
that supports the development of lecturer performance. The leadership style possessed by leaders in universities
determines whether an institution develops. The revolutionary era 4.0 that must be faced by universities had an
impact on changes in the pattern of appropriate leadership styles to be implemented to support lecturer learning
performance (Handayani et al., 2019). From various leadership theories, the style of participatory altruistic
leadership can be a reference for university leaders. The participatory altruistic leadership style will be perfect if it is
collaborated with the path goal and spiritual leadership style. (Hussain et al., 2016; Kardoyo et al., 2018; Hallinger &
Hammad, 2019; Pio & Tampi, 2018; Saide et al., 2019; Pourmola et al., 2019). Waheed and Khaur (2016)
indentifyng the quality knowledge into intrinsic, contextual and actionable qualities. Referring to the learning
http://ijhe.sciedupress.com International Journal of Higher Education Vol. 9, No. 5; 2020
Published by Sciedu Press 347 ISSN 1927-6044 E-ISSN 1927-6052
performance theory, learning performance is formally defined as the value of the set of lecturer behaviors that
contribute, either positively or negatively, to organizational goal accomplishment (Hussain et al., 2016). Those
behaviors are generally fit into three broad categories to organization(Kumpulainen et al., 2019; Purwanto et al.,
2019). Task performance includes the behavior of employees who are directly involved in the transformation of
organizational resources(Handayani et al., 2019).
1.2 Framework Analysis
Based on the novelty concept of learning performance, which gave rise to a new concept of smart working this study
will discuss the relationship and its influence between participatory altruistic leadership, quality knowledge, and
competence of lecturers performance(Famakin & Abisuga, 2016). Each of these leadership styles is taken in one
aspect and combined into participatory altruistic leadership as novelty in research. Some research questions are
formulated as following: there is a relationship between the quality knowledge with smart working. There is an
influence between the competence of lecturers on smart working. There is an influence between participatory
altruistic leadership to smart working. There is an influence between smart working on lecturer performance. There
is an influence on the quality knowledge on the learning performance. There is an influence between participatory
altruistic leadership on learning performance (Male et al., 2019). There is an influence between lecturer competence
on learning performance. Lecturer competencies which include pedagogical competence, professional competence,
social competence and personality will influence lecturers' behavior and performance including lecturer learning
performance (Sutarto et al., 2017). Indirectly both the quality knowledge, competence of lecturers and participatory
altruistic leadership will form a situation and a good understanding of the lecturers, namely intelligent performance
and subsequently expected to have an impact on lecturer learning performance (Purwanto et al., 2019). This explains
that there is a tendency for lecturer learning performance to be influenced by the quality knowledge, lecturer
competence and participatory altruistic leadership through the intelligent learning performance (Pio & Tampi, 2018).
The following will explain the relationship between variables in research on figure 1.
Figure 1. Framework of thinking
1.3 Hypothesis
H1: there is relationship between competence and smart working.
H2: there is relationship between participatory altruistic leadership and smart working
H3: there is relationship between quality knowledge and smart working
H4: there is relationship between smart working and learning performance
H5: there is relationship between quality knowledge and leraning performance
H6: there is relationship between participatory altruistic and learning performance
H7: there is relationship between competence and learning performance
2. Method
The population in this study were lecturers in the Civil Engineering Education Study Program throughout Indonesia.
The questionnaire instrument was carried out on 76 respondents. The data collection technique of this research was
carried out using questionnaire technique. This technique is done by using a questionnaire to reveal the data needed
in research that includes data: altruistic participatory leadership, quality knowledge, lecturer competence, smart
Smart Working
Participatory Altruistic
Knowledge Quality
Competence
Learning performance
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Published by Sciedu Press 348 ISSN 1927-6044 E-ISSN 1927-6052
working and lecturer learning performance. Questionnaires were distributed online because of the Covid-19
pandemic
Analysis of the data used in this study is the full model of Structural Equation Modeling (SEM) by first testing its
dimensions with confirmatory factor analysis which is the first step in the SEM analysis process. Confirmatory
Factor Analysis is a form of a measurement model that models the relationship variables. The purpose of the
measurement model is to describe how well these indicators can be used as instruments for measuring variables. In
Structural Equation Modelling (SEM) analysis, the relationship between variables and observed variables is
reflective, where the observed variables are a reflection of variables (Milhem, Muda, & Ahmed, 2019)
After checking all of estimation carefully, the researcher did not find more than one negative error variance and
standard of loading factors. In addition there is no standard error of great value. With these results, all variables have
met good conditions in the absence of an offending estimate (Sarstedt et al., 2019). Test the validity and reliability in
the SEM analysis on the Lisrel program can be done using a measurement model. Combination of all SEM
components into a complete model flowcharts (Path Diagram) or Hybrid Model. Path diagram describe the research
model in the form of mathematical notation (Sarstedt et al., 2019). This model shows the relationship between
indicator variables and their variables in the Pathway Hybrid Model as shown in Figure 2
Figure 2. Pathway Hybrid Model
Figure 2 shows the estimated coefficient value of the relationship between variables namely φ12 = regression of
participatory altruistic toward quality knowledge, φ13= regression of participatory altruistic toward competence,
φ23= regression of quality knowledge toward competence, γ14= regression of participatory altruistic toward smart
working, γ24= regression of quality knowledge toward smart working, γ34= regression of competence toward smart
working, γ15= regression of participatory altruistic toward learning performance, γ25= regression of quality
knowledge toward learning performance, γ35= regression of competence toward learning performance, β45=
regression of smart working toward learning performance. After knowing the estimated coefficient value, the next
step is to calculate the t value, to determine whether the research model hypothesis is accepted or no accepted.
3. Results
Structural model testing is related to evaluation of the coefficients or parameters that show a causal relationship or
the effect of one variable on another variable. In this research, testing of the model is carried out to find out how
participatory altruistic, quality knowledge, competence and smart working with learning performance. Results of the
structural model analysis are shown in Table 1.
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Published by Sciedu Press 349 ISSN 1927-6044 E-ISSN 1927-6052
Table 1. Evaluation of Structural Model Coefficients and T-value on the Hypothesis
Hypothesis
Regression
Coefficient
T-value
Result
(t>1.96)
H1 : there is a positive relationship between
competence and smart working.
0.80
3.18
Accepted
H2 : there is a positive relationship between
participatory altruistic leadership and smart
working
0.86
3.57
Accepted
H3 : there is a positive relationship between quality
knowledge and smart working
0.81
4.19
Accepted
H4 : there is a positive relationship between smart
working and learning performance
0.99
3.69
Accepted
H5 : there is a positive relationship between quality
knowledge and leraning performance
0.91
3.62
Accepted
H6: there is a positive relationship between
participatory altruistic and learning performance
0.88
4.61
Accepted
H7: there is a positive relationship between
competence and learning performance
0.88
4.70
Accepted
Table 3 shows that all proposed hypotheses are accepted significantly. The first hypothesis, namely there is a positive
relationship between competence and smart working. Accepted because the t-value obtained was 3.18 and the
regression coefficient was 0.80. The value to be significant because the t-value >1.96 and the estimated value is quite
high because of the positive relationship between the competence and smart working indicators. In the analysis of
structural from standard solution path diagram hybrid model between participatory altruistic and smart working, it
can be seen that the second hypothesis is accepted. Because there is a positive relationship between participatory
altruistic and smart working. Accepted because the t-value obtained was 3.57 and the regression coefficient was 0.86.
The value to be significant because the t-value >1.96 and the estimated value is quite high due to a positive
relationship between the participatory altruistic and smart working indicators. Analysis between variables quality
knowledge and smart working, it is known that the regression coefficient and t-value obtained show significant
results. This can be seen from the regression coefficient of 0.81 which is quite high and t-value of 4.19 which is
greater than 1.96. In the structural of standard solution path diagram hybrid model analysis between the variables
smart working and learning performance, it is known that the regression coefficient and t-value obtained show
significant results. This can be seen from the regression coefficient of 0.99 and t-value of 3.69 where the t-value is
greater than 1.96. In the structural of standard solution path diagram hybrid model analysis between variables quality
knowledge and learning performance, it is known that the regression coefficient obtained is 0.91 and the t-value is
3.62 which is greater than 1.96. These results indicate that there is a significant relationship between the latent
variables quality knowledge and learning performance, so this proves that hypothesis 5 is accepted. Significant
results in hypothesis 6 prove that there is a positive relationship between participatory altruistic learning performance,
so it can be said that the research hypothesis 6 is accepted. It is known that the regression coefficient and t-value
obtained show significant results. This can be seen from the regression coefficient of 0.88 which is quite high and
t-value of 4.61 which is greater than 1.96. In the analysis of structural from standard solution path diagram hybrid
model between variables competence and learning performance, it can be seen that there is a positive relationship
between competence and learning performance. Accepted because the t-value obtained was 4.70 and the regression
coefficient was 0.88. The value is said to be significant because the t-value > 1.96 and the estimated value is quite
high due to a positive relationship between the variables competence and learning performance.
4. Discussion
All three variables in research, competence, quality knowledge and leadership will shape smart working lecturer, so
that it will provide direction and quality in its learning performance. This condition will directly provide work results,
work performance and performance which is positive and tends to increase. The success of a university depends on
human resources in doing its work. This is determined by a positive attitude characterized by smart working. Smart
working is an adaptive behavior related to the development of knowledge. Smart working is directed to develop and
use knowledge in work situations. Smart working is based on the view that intelligence must be considered in the
http://ijhe.sciedupress.com International Journal of Higher Education Vol. 9, No. 5; 2020
Published by Sciedu Press 350 ISSN 1927-6044 E-ISSN 1927-6052
context of the situation between other mental preparations, demanding self-confidence, and behavior change and
behavior adjustment to the task at hand (Babalola et al., 2016). A good work ethic determines the success and
implementation of smart working. Attitudes, behaviors, smart working culture that is collaborated with the
development of professionalism into intellectual capital and positive emotional capital for lecturer learning
performance. The results of the study by Ferdinand (2004) state that the success of human resources in doing their
work is determined by a positive work attitude which is characterized by hard work attitudes, smart work attitudes
and aggressive work attitudes (hard-working, smartworking, agreiveness).
The results of this study are supported by the results of research by Widodo (2015) where indicators in the quality of
knowledge affect one's intelligence. The three criteria for using knowledge for innovation are credibility, relevance
and adaptability. In their research on Knowledge Quality Development Model Based on Knowledge Networks and
Cross-Functional Collaboration Towards Innovative Performance found that the first priority of performance
development models is to improve the quality of knowledge accurately, objectively, dynamically and reliably. one's
intelligence. The equation with this study is a performance review based on the quality of knowledge.
Thus the influence of lecturer competence on learning performance is supported by several research results
Competence which consists of variables including professionalism, social, pedagogy, personality stimulates the
lecturer to use the skills and potentials that are owned by smart working in carrying out their duties (Harro et al.,
2016).
Lecturers will use their abilities as an implementation of the quality of their knowledge to be able to innovate, act
and carry out useful activities at the university (Nasir et al., 2018).
This altruistic participatory leadership refers on the concept of leadership that has a voluntary spirit in leading
lecturers in the study program, by opening opportunities for lecturers to develop strategies and find solutions to
existing problems in the Sipil Engineering Education Study Program which includes several aspects namely
decisions, listeners and good hope givers are very important. In the context of learning activities, leadership is very
important, because in the world of education is loaded with things that do require someone works with heart,
voluntarily doing things that are possible more than its obligations, so that it can be well received in the environment
his work With this altruistic participatory leadership expected can provide motivation, foster a conducive situation in
the environment job, which is expected to further the lecturer learning performance conducive, besides other factors
that support (Kardoyo et al., 2019). Leader's style and power Altruistic participatory is expected to be a role model
that can be supervisors for lecturers and have expertise, which will have an impact to the desire of lecturers to be
individual learners who will always be improving the competence and knowledge quality positively influences on its
performance.
5. Conclusion
This research has led to a new concept of learning performance of lecturers. Influence between leadership The
quality knowledge, competence of lecturers and smart working on the learning performance of lecturers.
Participatory altruistic leadership is expected to be creating conditions conducive to lecturer learning performance.
Quality indicator lecturer knowledge which includes the quality of intrinsic knowledge, quality Conceptual
knowledge and actionable quality, will influence patterns and innovation lecturers in behaving, acting and
implementing in universities and this tends to be affect the performance of lecturers. Thus the lecturer competence
which includes pedagogical competence, professional competence, and social competence personality will influence
the behavior and performance of lecturers' learning performance. This provides an explanation that lecturer learning
performance is influenced by the quality of lecturer knowledge, lecturer competence and participatory leadership
altruistic through smart working lecturers.
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