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PSYCHOLOGY AND EDUCATION (2022) 59(2): 909-921
ISSN: 1553-3969
909
www.psychologyandeducation.net
The impact of inquiry-based learning on problem-solving skills and
conceptual knowledge building
Dr. Majlinda Hala1*, Assoc. Prof. Dr. Nazmi Xhomara2
1Lecturer, Department of Picture, Faculty of Arts, University of Arts, Tirana, Albania.
2 Lecturer, Department of Mathematics and Statistics, Faculty of Information Technology and Innovation, Luarasi University,
Albania.
*majlindahala@gmail.com
nazmixhomara@hotmail.com
ABSTRACT
The study aims to examine the implementation of an inquiry-based learning approach to improving problem-solving skills and
conceptual knowledge building at university. Analysis of Variance (ANOVA) was used to test the impact of inquiry-based
learning in problem-solving skills and conceptual knowledge building. The study found that that variance of the inquiry-based
learning is different, revealing that different levels of inquiry-based learning influence problem- solving. It is also found that
approximately 88.5% of the variance in problem- solving can be explained or accounted for by inquiry-based learning differences.
It is confirmed that that variance of the inquiry-based learning is different, revealing that different levels of inquiry-based learning
influence conceptual knowledge building. The study also found that approximately 31.5% of the variance in conceptual
knowledge building can be explained or accounted for by inquiry-based learning differences.
Keywords
Inquiry-based learning, problem-solving, conceptual knowledge building
Introduction
The inquiry-based learning approach used by
lecturers is supposed to be one of the important
variables that influence problem-solving skills and
conceptual knowledge building in the university.
Inquiry-based learning is associated with some
educational philosophies or paradigms; fostering
communities of learning, learning by design,
central conceptual structures, direct instruction,
higher-order thinking skills, and knowledge
building (van den Broek, 2012). It has often been
found that students appreciate hands-on work, and
find that they learn more with courses that include
a project than those relying solely on conventional
lectures and tests (Auerbach, Concordel,
Kornatowski & Floreano, 2019). Attention to
inquiry-based teaching practices has surfaced as
one vehicle for supporting the development of
critical thinking skills in science classrooms
(Achieve Inc., 2013, cited by Franco, 2013). In
science education, inquiry-based approaches to
teaching and learning provide a framework for
students to building critical-thinking and problem-
solving skills (Roehrig, Michlin, Schmitt,
MacNabb & Dubinsky, 2012). Inquiry-based
teaching is at the heart of several pedagogical
initiatives including project-based instruction,
maker-centered learning, and the 5E learning
cycle: engagement, exploration, explanation,
elaboration, and evaluation (Bybee et al., 2006,
cited by Rodriguez, Allen, Harron & Qadri, 2019).
Inquiry-based teaching aims to increase student
engagement through the development of hands-
on, minds-on skills, such as critical thinking,
collaboration, and communication, needed for the
21st century (The Partnership for 21st Century
Skills, 2015). This approach respects the
complexities of the learning process, values the
knowledge and experience students bring to the
classroom, and prioritizes active problem-solving
communication of findings, and the shared
construction of new ideas (Rodriguez, Allen,
Harron & Qadri, 2019).
At the same time, students’ academic gain and
learning performance are affected by teaching
faculty, students schooling, family social status,
residential area of students, the medium of
instructions in schools, and daily study hour
(Xhomara, 2018). To compete globally in the 21st
Century, students must have the skills to design
their projects and understand how to navigate the
wealth of information available at their fingertips.
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One of the most important tools is to be able to
investigate ideas and implement a plan of action
to answer questions that have not been explored.
These creative problem-solving skills are essential
when students design problems and projects
during the student-driven inquiry (Doss, 2018).
Kraut (2015) pointed out that the inverted
classroom allows more in-class time for inquiry-
based learning and for working through more
advanced problem-solving activities than does the
traditional lecture class. Developing problem-
solving skills is often accepted as a desirable goal
in many educational settings. However, there is
little evidence to support that students are better
problem-solvers after graduating. The students
can solve routine problems, but they confronted
difficulties when adapting their prior knowledge
for the solution of new problems (Fadzil, 2017).
The study aims to investigate the implementation
of an inquiry-based learning approach to
improving problem-solving skills and conceptual
knowledge building at university level. The
research questions are as follows: (1) Do different
levels of inquiry-based learning differ in terms of
problem-solving skills? Are inquiry-based
learning higher levels better adjusted than lower
levels in terms of problem-solving skills? (2) Do
different levels of inquiry-based learning differ in
terms of conceptual knowledge building? Are
inquiry-based learning higher levels better
adjusted than lower levels in terms of conceptual
knowledge building?
Theoretical framework and Literature review
The most important factors in the teaching and
learning process are an immature, undeveloped
being; and certain social aims, meanings, values
incarnate in the matured experience of the adult.
The educative process is the due interaction of
these forces. The current standpoint of the
students and the facts and truths of studies define
instruction. (Dewey, 1902). Constructivism theory
is used as a basis of the theoretical framework.
Constructivism is an instruction paradigm posits
that learning is an active, constructive process,
and where the learner is a constructor, and
actively create their subjective representations of
reality (David, 2015).
Conceptual framework
The conceptual framework for the study, as shown
in figure 1, is developed from a review of existing
evidence about the relationship between the
interested variables. The review including a search
for relevant empirical research through Sage,
ERIC, and EBSCO, using the keywords inquiry-
based learning, problem-skills, and conceptual
knowledge building. The results of the study were
interpreted in terms of constructivist theory and
research conducted in the field.
Figure 1. Conceptual framework
Literature review
The impact of inquiry-based learning on problem-
solving skills
Inquiry-based learning in university education is
thought to be one of the most important variables
to increase problem-solving skills in university
studies. Many authors have done a lot of research
to investigate the relationship between inquiry-
based learning and problem-solving skills in
university studies.
O'Neill, Adams, Bandelt, Chester, Cai, &
Nadimpalli (2019) pointed out that conventional
methods and methodologies may function as
starting points, but they lack a focus on the
metacognition and inquiry-based thinking
required to analyze, evaluate, and synthesize
diverse problems; meanwhile, Fadzil (2017)
confirmed that when students are engaged in the
inquiry-based learning process, the knowledge can
be generated more meaningfully than in other
perceived passive mode of learning. The inquiry-
based learning that is based on the cognitive
approach and student-centered teaching impact
high-level cognitive skills, such as critical-
creative thinking and problem-solving rather than
conventional teacher-centered teaching (Akman &
Alagöz, 2018; Yu, 2015); and Hassi and Laursen
(2015) revealed that learning in classroom
situations that use student activity, deep
engagement, and collaboration not only enhance
students' thinking and problem-solving skills, but
it also significantly promotes self-perceptions, and
social skills.
The problem-solving skills are influenced by the
inquiry-based learning approach (Yuliati,
Riantoni, & Mufti, 2018; Turnip, Wahyuni &
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Tanjung, 2016); and Davis (2018), as well as
Xhomara (2019) found out that inquiry-based
learning approach influence higher ratings in
problem-solving skills, life skills and
students’achievements compared with the lecture-
based approach. Roehrig, Michlin, Schmitt,
MacNabb, & Dubinsky (2012) found out that
combined content and knowledge of learning with
inquiry-based pedagogy impact students' inquiry-
based practices; and Thang, & Koh (2017)
showed that the integrated science module
deepened students' confidence with self-directed
learning and authentic problem-solving whereas
students' confidence with critical thinking
positively predicted students' end-of-year results.
The use of inquiry-based activities might have
helped learners improve their level (Bozkurt &
Koc, 2020); and including project-based
instruction, maker-centered learning, and the 5E
learning cycle: engagement, exploration,
explanation, elaboration, and evaluation impact
concept learning (Rodriguez, Allen, Harron, &
Qadri, 2019).
Großmann & Wilde (2019) shows that inquiry-
based experimentation influence knowledge
acquisition on students with low prior knowledge;
meanwhile, Zhang & Li (2019) found out that the
inquiry-based investigation as an instructional
approach was associated with students' overall
science achievement and achievement in cognitive
domains, including knowing science facts,
applying scientific principles, and reasoning with
scientific concepts to solve problems. In the
inquiry-based learning, and where students
become completely engaged, they work logically
and systematically and learn to use problem-
solving and communication skills, such as
scientific practices of hypothesizing,
investigating, observing, explaining, and
evaluating (Cherif, Siuda, Kassem, Gialamas &
Movahedzadeh, 2017; Doss, 2018). The prior
knowledge, problem-based teaching, the
comprehensive learning approach and assessment
explained 50% of the variance in the levels of
basic-learning skills (Xhomara, 2020); at the same
time, Rapanta (2018) shows that the Socratic
method of inquiry, collaborative problem solving,
and debate-based deliberation establishing the
relationship with the strategic promotion of
argumentative reasoning; but from the other point
of view, McRae-Jones (2017) revealed that there
was no impact between the inquiry-based
instructional strategies and student achievement in
social studies.
Inquiry-based learning approach support reflective
skills of the pre-service teachers (Østergaard,
2019); as well as cognitive development, higher
motivation to learn, and increased self-efficacy of
students (McElvain & Smith, 2016). Inquiry-
based projects develop a natural curiosity of
students that will lead them on the path toward
solving problems (Cook, Hartman, Pierce &
Seaders, 2017; LaBanca & Ritchie, 2011);
meanwhile, Méndez & Pérez Gómez (2017)
pointed out that inquiry-based practicum in the
education of future teachers has been identified as
a key component to foster student-
teachers'abilities to face problems, try to solve
them. Worthington (2018) emphasized that the
student-centered teaching and learning
opportunities can improve students' critical
thinking, problem-solving, and collaborative
skills; meanwhile, Falloon (2017) found out that
student thinking, problem-solving and
collaboration were increased when using digital
tablets for a range of conventional curriculum-
related purposes, and problem and inquiry-based
learning programs.
Inquiry-based learning through robotics
applications and virtual learning system offers
multiple possibilities for students to implement
their ideas, and influence problem-solving and
improve the effectiveness of online learning
(Auerbach, Concordel, Kornatowski, & Floreano
(2019; Chanprasitchai & Khlaisang, 2016; Avsec
& Kocijancic, 2016). Gupta (2012) found out that
an inquiry-based approach to learning and
teaching and student-centered active learning
approach may be the effective way to enhance
student understanding of concepts; and Gillies,
Nichols, Burgh & Haynes (2012) shows that
teaching students to ask and answer questions is
critically important if they are to engage in
reasoned argumentation, problem-solving, and
learning. The student-centered construction of
learning and knowledge, and inquiry-based
teaching approaches support students to solve
authentic problems by thinking critically, and
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actively create content (Jansen, 2011; Drake &
Long, 2009); and Nehring, Nowak, zu Belzen &
Tiemann (2015) show that students' characteristics
predict their inquiry skills to a large extent (55%),
whereas 9 out of 12 variables contribute
significantly on a multivariate level. Thus, it is
evidenced that inquiry-based learning impacts
problem-solving skills at university. In
conclusion, the investigation of the relationship
between inquiry-based learning and problem-
solving skills, as resulted in previous research, is
important. Therefore, based on the above
literature review it is hypothesized that:
H # 1: Problem-solving is a function of inquiry-
based learning
The impact of inquiry-based learning on
conceptual knowledge building
Inquiry-based learning in university education is
thought to be one of the most important variables
to increase conceptual knowledge building in
university studies. Many authors have done a lot
of research to investigate the relationship between
inquiry-based learning and conceptual knowledge
building in university studies.
Inquiry projects and extensive in-service
professional development had positive effects on
students' understanding of the complexity of
educational concepts (Byker, Coffey, Harden,
Good, Heafner, Brown & Holzberg, 2017); and
Arslan Buyruk & Ogan Bekiroglu (2018)
indicated that model-based inquiry on pre-service
teachers' conceptual understanding of concepts
facilitates conceptual learning; meanwhile, the
observation and analysis of scientific data can be
used as a scaffold to build conceptual
understanding in science through inductive
reasoning (Nichol, Szymczyk & Hutchinson,
2014; Levy & Petrulis, 2012). Xhomara (2020)
demonstrated that students' academic success has
been explained strongly by individual study work
and lecturer support; at the same time, Lai (2017)
indicate that a supportive online learning
environment entails teachers using effective
pedagogical practices to meet the needs of their
students and to foster learner motivation and
engagement; and Vokatis & Zhang (2016) found
out that engaged in inquiry-based classroom
practice using knowledge building pedagogy and
knowledge forum, a collaborative online
environment influence on deep and lasting change
requires teacher transformation and capacity
building. Project-based learning offers teachers a
model for students to develop and enact inquiry-
based projects that reflect positive, and active,
civic dispositions (LeCompte & Blevins, 2015);
meanwhile, Salsabila, Wijaya & Winarno, 2019)
found out that argument-driven inquiry impact
students' sustainability awareness in learning.
Tezcan-Unal, Winston & Qualter (2018) pointed
out that supportive learning environment, learning
practices, and leadership supports learning; and
Kiss & Wang (2017) found out that the
implementation of knowledge building pedagogy
has a positive impact on teacher questioning and
contributes to creating an effective learning
environment. Kovanovic, Gaševic & Hatala
(2014) shows that inquiry-based learning and the
specifics of communication through asynchronous
discussions support the student interactions with
information and technology; meanwhile,
Williams, Pringle & Kilgore (2019) revealed that
engaging in practitioner inquiry, tapped into the
potential of deliberate cognate instruction support
the learning of science within the context of
inquiry-based science teaching. Inquiry-based
instruction, as well as team teaching support
students to construct knowledge (Musanti, 2017;
Bierenstiel & Snow, 2019); meanwhile, Arce,
Bodner & Hutchinson (2014) point out that
extensive in-service professional development can
produce a substantive change in teachers' beliefs
about optimum teaching practice. Xhomara (2022)
found out that there is a strong positive correlation
between student-centred teaching and critical
thinking skills; meanwhile, Van Booven (2015)
shows that the fixed nature of authoritatively
oriented questioning can dramatically limit
students' opportunities to demonstrate higher-
order scientific understanding; and Reeves,
Fostvedt, Laugerman, Baenziger, Shelley, Hand &
Therrien, 2013) indicate that inquiry-based
approach increases cognitive abilities such as
critical thinking. Nilssen & Solheim (2015)
confirmed that bridging theory and practice is
depended by commuting between field practice
and coursework, the authenticity of the tasks and
future relevance for the teaching; meanwhile,
Herczog (2014) showed that inquiry-based
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teaching impact building the critical thinking,
problem-solving, and participatory skills of
students. Thus, it is evidenced that inquiry-based
learning impacts conceptual knowledge building
at university. In conclusion, the investigation of
the relationship between inquiry-based learning
and conceptual knowledge building, as resulted in
previous research, is important. Therefore, based
on the above literature review it is hypothesized
that:
H # 2: Conceptual knowledge building is a
function of inquiry-based learning.
Methodology
Method and design
The quantitative approach was the method
used in the research. The design of the study
employed a sample of 132 law students. Inquiry-
based learning was selected to be used as an
independent variable; meanwhile, problem-
solving and conceptual knowledge building were
selected as dependent variables. Inquiry-based
learning, as an independent variable has five
levels: 1=very low level, 2= low level, 3= medium
level, 4= high level, 5= very high level. Problem-
solving skills, as dependent variable has five
levels: 1= 0-40 scores, 2= 41-60 scores, 3= 61-80
scores, 4= 81-90 scores, 5= 91-100 scores.
Conceptual knowledge building, as the dependent
variable has also five levels: 1=very low level, 2=
low level, 3= medium level, 4= high level, 5=
very high level.
Sample and data collection
A non-random sample of 132 law students
was selected to be investigated in the research.
Regarding the study program, 76 respondents
(57.6%) study in the Civil Law program,
meanwhile, 56 of the experimental group (42.4%)
study in the Criminal Law program. The sample
of respondents is composed of 80 females
(60.6%), and 52 (39.4%) males. A structured
questionnaire was used to gather the primary data
from the students in the 2019-2020 academic year.
The questionnaire is based on academic self-
efficacy, achievement motivation, engagement
online survey (Huang, 2011) and is modified,
piloted, and validated by the author. The
questionnaire used in the research is compounded
by three main dimensions: (1) inquiry-based
learning, (2) problem-solving, and (3) conceptual
knowledge building. Alfa Cronbach's values of
questionnaire scales vary from .83 to .95
confirming a very good value of reliability, as
follows.
Table 1.
Cronbach's alpha values
Table 1.
Cronbach's alpha values
N0.
Variables
Alpha
Cronbach
value
Evaluation
1
Inquiry-based
learning
.95
Excellent
2
Problem-
solving skills
.88
Good
3
Conceptual
knowledge
building
.83
Good
Analysis
Central tendency values, as well as frequency
values, were used to describe the inquiry-based
learning, problem-solving, and conceptual
knowledge building. A one‐way fixed effects
between-subjects analysis of variance (ANOVA)
was conducted to evaluate the null hypothesis that
problem- solving, and conceptual knowledge
building population means were equal across five
inquiry-based learning levels. Preliminary
assumption testing was conducted to check for
normality, linearity, univariate outliers,
homogeneity of variance, and multicollinearity,
with no violations noted.
Results and Discussion
Descriptive statistics
Table 2.
Inquiry-based learning frequencies
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Table 2.
Inquiry-based learning frequencies
Inquiry-based learning
Frequency
Percent
Valid
Percent
Cumulative
Percent
Valid
Very low level
16
12.1
12.1
12.1
Low level
24
18.2
18.2
30.3
Medium level
20
15.2
15.2
45.5
High level
40
30.3
30.3
75.8
Very high level
32
24.2
24.2
100.0
Total
132
100.0
100.0
Inquiry-based learning’ frequencies
indicate that 30.3% of the respondents report very
low and low level in inquiry-based learning;
15.2% of them medium level; meanwhile, 54.5%
of the respondents report high and very high level.
Central tendency values for experimental groups
(M= 3.3636, SD = 1.34943), indicate the same
tendency for values as measured by frequencies.
Therefore, the most of respondents report high
and very high levels; meanwhile, approximately
one-third of them report the very low and low
level in inquiry-based learning.
Table 3.
Problem- solving frequencies
Table 3.
Problem- solving frequencies
Problem- solving
Frequency
Percent
Valid
Percent
Cumulative
Percent
Valid
Very low level
8
6.1
6.1
6.1
Low level
32
24.2
24.2
30.3
Medium level
24
18.2
18.2
48.5
High level
52
39.4
39.4
87.9
Very high level
16
12.1
12.1
100.0
Total
132
100.0
100.0
Problem-solving’ frequencies indicate that
6.1% of the respondents report 0-40 scores in
problem-solving; 24.2% of them 41-60 scores;
18.2% of them 61-80 scores; 39.4% of them 81-90
scores; meanwhile, 12.1% of the respondents
report 91- 100 scores. Central tendency values for
experimental groups (M= 3.2727, SD = 1.34978),
indicate the same tendency for values as measured
by frequencies. Therefore, the most of
respondents report high and very high levels;
meanwhile, approximately one-third of them
report the very low and low level in problem-
solving.
Table 4.
Conceptual knowledge building frequencies
Table 4.
Conceptual knowledge building frequencies
Conceptual knowledge building
Frequency
Percent
Valid
Percent
Cumulative
Percent
Valid
Very low level
16
12.1
12.1
12.1
Low level
20
15.2
15.2
27.3
Medium level
40
30.3
30.3
57.6
High level
32
24.2
24.2
81.8
Very high
level
24
18.2
18.2
100.0
Total
132
100.0
100.0
Conceptual knowledge-building’
frequencies indicate that 27.3% of the respondents
report very low and low level in conceptual
knowledge building; 30.3% of them are medium
level, meanwhile, 42.4% of the respondents high
and very high level of conceptual knowledge
building. Central tendency values for
experimental groups (M= 3.2121, SD = 1.25419),
indicate the same tendency for values as measured
by frequencies. Therefore, less than half of
respondents report high and very high level;
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meanwhile, approximately one-third of them
report the very low and low level in conceptual
knowledge building.
Inferential statistics
Test of Hypothesis
H # 1: Problem- solving is a function of inquiry-
based learning
Table 5.
Levene's Test of Equality of Error’ outputs
Table 5.
Levene's Test of Equality of Error’ outputs
Levene's Test of Equality of Error
Variances
Dependent Variable: PS
F
df1
df2
Sig.
24.734
4
127
.000
Tests the null hypothesis that the error
variance of the dependent variable is equal
across groups.
a. Design: Intercept + IBL
Since the Levene's Test of Equality of
Error Variances is statistically significant (p =
.000), as shown in table 5, there is evidence to
reject the null hypothesis of equality of variance
across groups of the inquiry-based learning’
independent variable. This result suggests that
somewhere among the variances in the population,
there is an inequality. Therefore, different levels
of inquiry-based learning influence problem-
solving.
Table 6.
Tests of Between-Subjects Effects’outputs
Table 6.
Tests of Between-Subjects Effects’outputs
Tests of Between-Subjects Effects
Dependent Variable: PS
Source
Type III
Sum of
Squares
df
Mean
Square
F
Sig.
Partial
Eta
Squared
Corrected
Model
150.682a
4
37.670
245.341
.000
.885
Intercept
1051.559
1
1051.559
6848.618
.000
.982
IBL
150.682
4
37.670
245.341
.000
.885
Error
19.500
127
.154
Total
1584.000
132
Corrected
Total
170.182
131
a. R Squared = .885 (Adjusted R Squared = .882)
As shown in table 6, a statistically
significant difference was found (F = 37.670 on 4
and 127 df, p < 0.001), with an estimated effect
size of 0.885 (Eta squared). This result suggesting
that approximately 88.5% of the variance in
problem- solving can be explained or accounted
for by inquiry-based learning differences.
Therefore, based on ANOVA outputs, H # 1:
Problem- solving is a function of inquiry-based
learning, is supported. The result was consistent
with some previously reported works, who argued
that problem- solving is a function of inquiry-
based learning scores (Fadzil, 2017; Akman &
Alagöz, 2018; Yu, 2015; Hassi & Laursen, 2015;
Yuliati, Riantoni, & Mufti, 2018; Turnip,
Wahyuni & Tanjung, 2016; Davis, 2018; Thang,
& Koh, 2017; Großmann & Wilde, 2019; Zhang
& Li, 2019; Cherif, Siuda, Kassem, Gialamas &
Movahedzadeh, 2017; Doss, 2018; Cook,
Hartman, Pierce & Seaders, 2017; LaBanca &
Ritchie, 2011; Méndez & Pérez Gómez, 2017;
Worthington, 2018; Auerbach, Concordel,
Kornatowski, & Floreano, 2019; Chanprasitchai &
Khlaisang, 2016; Avsec & Kocijancic, 2016;
Jansen, 2011; Drake & Long, 2009). As a
conclusion, different levels of inquiry-based
learning influence problem- solving.
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H # 2: Conceptual knowledge building is a
function of inquiry-based learning
Table 7.
Levene's Test of Equality of Error’ouputs
Table 7.
Levene's Test of Equality of Error’ouputs
Levene's Test of Equality of Error
Variances
Dependent Variable: CKB
F
df1
df2
Sig.
5.247
4
127
.001
Tests the null hypothesis that the error
variance of the dependent variable is
equal across groups.
a. Design: Intercept + IBL
Since the Levene's Test of Equality of
Error Variances is statistically significant (p =
.001), as shown in table 7, there is evidence to
reject the null hypothesis of equality of variance
across groups of the inquiry-based learning’
independent variable. This result suggests that
somewhere among the variances in the population,
there is an inequality. Therefore, different levels
of inquiry-based learning influence conceptual
knowledge building.
Table 8.
Tests of Between-Subjects Effects’outputs
Tests of Between-Subjects Effects
Dependent Variable: CKB
Source
Type III
Sum of
Squares
df
Mean
Square
F
Sig.
Partial
Eta
Squared
Corrected
Model
64.927a
4
16.232
14.606
.000
.315
Intercept
1110.084
1
1110.084
998.919
.000
.887
IBL
64.927
4
16.232
14.606
.000
.315
Error
141.133
127
1.111
Total
1568.000
132
Corrected
Total
206.061
131
a. R Squared = .315 (Adjusted R Squared = .294)
As shown in table 8, a statistically
significant difference was found (F = 16.232 on 4
and 127 df, p < 0.001), with an estimated effect
size of .315 (Eta squared). This result suggesting
that approximately 31.5% of the variance in
conceptual knowledge building can be explained
or accounted for by inquiry-based learning
differences. Therefore, based on ANOVA outputs,
H # 2: Conceptual knowledge building is a
function of inquiry-based learning, is supported.
The result was consistent with some previously
reported works, who argued that conceptual
knowledge building is a function of inquiry-based
learning scores (Arslan Buyruk & Ogan
Bekiroglu, 2018; Nichol, Szymczyk &
Hutchinson, 2014; Levy & Petrulis, 2012; Vokatis
& Zhang, 2016; LeCompte & Blevins, 2015;
Tezcan-Unal, Winston & Qualter, 2018; Williams,
Pringle & Kilgore, 2019; Musanti, 2017;
Bierenstiel & Snow, 2019; Reeves, Fostvedt,
Laugerman, Baenziger, Shelley, Hand & Therrien,
2013; Herczog, 2014). As a conclusion, different
levels of inquiry-based learning influence
problem- solving.
Conclusion and Implication
Several limitations of the study should be
acknowledged as part of the conclusion. First, the
measurement of inquiry-based learning, as well as
problem-solving skills and conceptual knowledge
building are made through using self- reported
PSYCHOLOGY AND EDUCATION (2022) 59(2): 909-921
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instruments. The study aimed to examine the
implementation of inquiry-based learning to
improving problem-solving skills and conceptual
knowledge building at university. The prior
assumption was that problem-solving skills and
conceptual knowledge building are a function of
inquiry-based learning.
It is found that the most of respondents reported
the high and very high level of inquiry-based
learning, as well as problem-solving skills,
meanwhile, approximately one-third of them
reported very low and low level. The study
showed that less than half of the respondents
reported the high and very high level of
conceptual knowledge building; meanwhile,
approximately one-third of them report the very
low and low level. The study found that that
variance of the inquiry-based learning is different,
revealing that different levels of inquiry-based
learning influence problem- solving. It is found
that approximately 88.5% of the variance in
problem- solving can be explained or accounted
for by inquiry-based learning differences. The
other variance may be explained by hidden or
unknown variables. It is confirmed that that
variance of the inquiry-based learning is different,
revealing that different levels of inquiry-based
learning influence conceptual knowledge building.
It is found that approximately 31.5% of the
variance in conceptual knowledge building can be
explained or accounted for by inquiry-based
learning differences. The other variance may be
explained by hidden or unknown variables.
The other variance may be explained by hidden or
unknown variables. The study confirmed that
inquiry-based learning makes the strongest unique
contribution to explaining problem- solving skills.
The study’s results, supported by other
investigators about the influence of inquiry-based
learning on the improving of problem-solving, and
conceptual knowledge building have implications
for future research. Future studies should
investigate the impact of other variables on the
improving of problem-solving, and conceptual
knowledge building. The results of this study also
have key implications in practice. The important
support should design to empower lecturers and
students because it is confirmed by this study that
inquiry-based learning influences the improving
of problem-solving, and conceptual knowledge
building. In all, the finding of this study support
theoretical and practical understanding as inquiry-
based learning is an important variable that
supports the improving of problem-solving, and
conceptual knowledge building.
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