Development of DIGaKiT: identifying students’ alternative conceptions by Rasch analysis model

Journal of Education and Learning (EduLearn)
Vol. 18, No. 1, February 2024, pp. 128~139
ISSN: 2089-9823 DOI: 10.11591/edulearn.v18i1.20970  128
Journal homepage: http://edulearn.intelektual.org
Development of DIGaKiT: identifying students’ alternative
conceptions by Rasch analysis model
Achmad Samsudin1
, Nurul Azizah1
, Nuzulira Janeusse Fratiwi1
, Andi Suhandi1
,
Irwandani Irwandani2
, Muhammad Nurtanto3
, Muhamad Yusup4
, Supriyatman Supriyatman5
,
Masrifah Masrifah6
, Adam Hadiana Aminudin7
, Bayram Costu8
1
Department of Physics Education, Faculty of Mathematics and Natural Sciences Education, Universitas Pendidikan Indonesia,
Bandung, Indonesia
2
Department of Physics Education, Faculty of Tarbiyah and Teacher Training, Universitas Islam Negeri Raden Intan Lampung,
Lampung, Indonesia
3
Department of Mechanical Engineering Education, Faculty of Teacher Training and Education, Universitas Sultan Ageng Tirtayasa,
Serang, Indonesia
4
Department of Physics Education, Faculty of Teacher Training and Education, Universitas Sriwijaya, Palembang, Indonesia
5
Department of Physics Education, Faculty of Teacher Training and Education, Universitas Tadulako, Palu, Indonesia
6
Department of Physics Education, Faculty of Teacher Training and Education, Universitas Khairun, Ternate, Indonesia
7
Department of Electrical Engineering, Faculty of Industrial Technology, Universitas Kebangsaan Republik Indonesia, Bandung,
Indonesia
8
Department of Science Education, Yildiz Technical University, Istanbul, Turkey
Article Info ABSTRACT
Article history:
Received May 24, 2023
Revised Aug 7, 2023
Accepted Aug 19, 2023
Alternative conceptions become obstacles in physics. However, it is difficult
to find instruments that can identify students' alternative conceptions,
especially in gases kinetic theory (DIGaKiT). The purpose of this research
was to development of diagnostic instrument of DIGaKiT in identifying
students’ alternative conceptions by Rasch analysis model. The research
method used the defining, designing, developing, and disseminating (4D).
The samples are 31 students (12 male students and 19 female students, their
ages were typically 16 years old) at one of the senior high schools at
Belitung. Rasch analysis was used to identify the validity, reliability, and
distribution of students' alternative conceptions. The result is that the level of
validity and reliability of the instrument is in a good category. Meanwhile,
alternative conceptions of the kinetic theory of gases can be identified in all
questions, and the questions with the highest alternative conceptions are
questions with code Q11 (77%) and the lowest are questions with codes Q1,
Q5, and Q6 (4%). Therefore, teachers must design learning processes that
can reduce students’ alternative conceptions of the kinetic theory of gases
material.
Keywords:
Alternative conceptions
Diagnostic instrument
DIGaKiT
Gases kinetic theory
Rasch model
This is an open access article under the CC BY-SA license.
Corresponding Author:
Achmad Samsudin
Department of Physics Education, Universitas Pendidikan Indonesia
Street of Dr. Setiabudi, No. 229, Isola, Sukasari, Bandung 40154, Indonesia
Email: achmadsamsudin@upi.edu
1. INTRODUCTION
Students do not originate in the classroom with unfilled attention, since they progress views about
belongings that occur in their environs from the very initial existences of their lives to any preceding life
involvement or observation, not essentially happening out of formal education. Repeatedly, students’ ideas are
dissimilar from acknowledged scientific knowledge that express as misconceptions, alternative structures,
alternative conceptions, common-sense concepts, pre-concepts, beliefs [1]–[3]. Several claims about alternative

J Edu & Learn ISSN: 2089-9823 
Development of DIGaKiT: identifying students’ alternative conceptions by … (Achmad Samsudin)
129
conceptions, they are: i) students come to classroom together through a varied customary of alternative
conceptions relating to ordinary substances and incidents, ii) the alternative conceptions that students convey
toward classroom expurgated across oldness, capability, gender, and social borders, iii) alternative conceptions
are obstinate and unaffected to destruction through conservative teaching approaches, iv) alternative
conceptions frequently corresponding descriptions of natural phenomena obtainable thru earlier groups of
experts and theorists, v) alternative conceptions take their backgrounds in a varied usual of individual
involvements comprising straight observation and perception, peer civilization, and verbal, in addition to in
educators’ descriptions and instructional resources, vi) teachers habitually contribute toward the identical
alternative conceptions as their students, vii) students’ previous acquaintance interrelates through information
obtainable in formal education, subsequent in a varied diversity of unintentional education consequences, and
viii) instructional methods that simplify conceptual change can be actual classroom apparatuses [4]–[6].
Students’ alternative conceptions contract through the usual world that is extremely unaffected to
modification from wrong and correct knowledge [7]–[9]. Moreover, students’ alternative conceptions
supposedly are pervasive, conducted deeply, and persevere over time [10]. Alternative conception is a blockade
for students to understand science for the reason that in numerous instances, alternative conceptions can hold
students to build correct ideas employed as the preliminary intuition for improved learning [11]. Thus,
alternative conceptions must be analyzing earlier using a diagnostic test. The diagnostic test employed
numerous procedures that record repeatedly for analyzing students’ alternative conceptions in science
education, such as open-ended tests [12], interviews [13], multiple-choice [14], and multiple-tier tests such as
two-tier test [15], three-tier test [16] and four-tier test [7]. Improvement of diagnostic tests on analyzing
students’ alternative conceptions shown in Figure 1. Each diagnostic test has advantages and disadvantages of
each.
Figure 1. Improvement of diagnostic tests to analyzing students’ alternative conceptions
Interviews have an important part because of their in-strength investigation and prospect of
explanation to acquire comprehensive reports of a student’s reasoning forms [17]–[19]. Interviewing is one of
the clearest and most commonly utilized methods to discover out the information and probable students’
alternative conceptions. The aim of interviewing is not to obtain responses to problems, although to discover
what students believe, what is in students’ way of thinking, and how students’ feelings about a concept.
Nevertheless, a substantial quantity of period is necessary to interview a sizeable total of the population in
demand to achieve bigger generalizability. Open-ended tests provide students with the opportunity to transcribe
their responses in their personal phrases and can be dispensed to greater tests. The open-ended test has
numerous benefits, explicitly assisting students communicate their opinions, allowing an infinite variety for
responses, decreasing in the responses offered by students [20]. However, it incomes time to examine the
outcomes and counting may be a problematic, complications in taking student responses, necessitating
particular skills for receiving expressive responses, roughly rejoinder responses may not be valuable, unfairness
responses may happen if students do not comprehend the subject of the interrogation [17].
Towards defeat troubles in the interview and open-ended test, multiple-choice tests take place to
evaluate student conception through sizable quantities of participants. The assistances of multiple-choice tests
are consents investigators to variety reporting of several subjects in a comparatively quick time, adaptable and
can be applied at diverse stages of tuition, unbiassed in evaluating responses and actuality consistent, and then
valued in evaluating students’ alternative conceptions [21]. Correspondingly, with conventional multiple-choice
tests the researcher cannot diﬀerentiate accurate responses expected to accurate perceptive as of individuals
owing toward inaccurate perceptive. Additionally, multiple-choice tests have numerous limitations such as
predicting can cause mistakes on modifications and split consistency, selections do not afford awareness and
considerate to students concerning their concepts [22].
Researchers protracted multiple-choice tests addicted to multiple-tier tests such as two-tier, three-tier
and four-tier. Two-tier tests can be restrained and connected to answers correlated to alternative conceptions.

 ISSN: 2089-9823
J Edu & Learn, Vol. 18, No. 1, February 2024: 128-139
130
Through two-tier tests, researchers can even discovery learner responses that have not been supposed of
previously [23]. Accordingly, two-tier tests might misjudge or undervalue students’ scientific understanding or
else miscalculate the scopes of the alternative conceptions subsequently lack of knowledge could not be
strongminded through the two-tier test [24]. The restrictions stated aimed at the two-tier tests were planned to be
remunerated by integrating a third tier. Through three-tier tests, alternative conceptions that are removed from a
lack of knowledge and faults can be evaluated [17]. Nevertheless, three-tier tests still cannot completely
distinguish the sureness selections intended for the key response from sureness selections for reasoning [7].
Consequently, may misjudge students’ scores and undervalue their absence of acquaintance. However, when
viewed from its strengths, the four-tier test is more effective for analyzing student alternative’ conceptions.
Four-tier tests can differentiate conceptions and correctly identify alternative conceptions, although it requires
more time when testing [25]. The four-tier test consists of four parts, the initial tier is answering selections, the
second tier is sureness grade for the initial tier, the third tier is the cause for the first tier, and the fourth tier is
sureness grade for the third tier.
The analyzing of students’ alternative conceptions have been done on physics concepts such as force
and motion [26]–[28], geometrical optics [17], electromagnetism [29], electric circuit [30], light wave [15], and
kinetic theory of gases [31]. This is caused by many physics concepts that is abstract, such as the kinetic theory
of gases for the basic laws (e.g., Avogadro, Boyle, Charles, and Gay-Lussac). Avogadro’s Law circumstances
that the volume of a gas is comparative to the quantity of molecules of the gas atom (𝑉 ∝ 𝑛). Boyle’s Law
circumstances that the volume of a gas is contrariwise comparative to the pressure when the temperature is
persistent (𝑉 ∝
1
𝑃
). Charles’s Law circumstances that volume is comparative to temperature when pressure is
persistent (𝑉 ∝ 𝑇). And then, Gay-Lussac’s Law circumstances that pressure is comparative to temperature
when the volume is persistent (𝑃 ∝ 𝑇). Concepts about temperature, volume, pressure, and the quantity of
molecules of the gas are abstract and potentially to inflict students’ alternative conceptions.
Alternative conceptions on the kinetic theory of gases can be analyzed through diagnostic test in
formula of four-tier test, named diagnostic instrument of Gases kinetic theory (DIGaKiT). This instrument was
examined through the Rasch model. The Rasch model qualified to Danish mathematician Georg Rasch [32].
Rasch model determinations to sustenance truthful quantity. Rasch model has been experienced to develop,
evaluate, and enable the intention of Rasch procedures that core to data examination and clarification of
additional guarantee [33]. Hence, the goal of this study was to developed DIGaKiT grounded on the Rasch
model.
2. METHOD
2.1. Sample and data collection
The samples are 31 students (12 male students and 19 female students, their ages were a typical of
16 years old) at single of senior high school at Belitung (or in English, Billiton), Indonesia. Belitung is one of
the islands which is included in the western part of Indonesia as shown in Figure 2. The sample was collected
by purposive sampling. The consideration practiced is students who have not yet learned about the kinetic
theory of gases.
Figure 2. Map of Tanjung Pandan, Belitung (by google map)

131
Figure 2 shows the current research position which can be used as a reference for further research on
the physics conception in Indonesia. The data was collected using the DIGaKiT. The instrument entails of 11
queries about the kinetic theory of gases in the form of four-tier test.
2.2. Research design
The research design was used defining, designing, developing, and disseminating (4D) model [34].
The design is the sequence that is carried out in this study. The details of the 4D model in this study are
shown in Figure 3.
Figure 3. The research design of 4D model
2.3. Analyzing the data
Data analysis was carried out in several stages. However, before evaluating the instrument using
Rasch model, the first step is categorized students’ conceptions. Students’ conceptions were categories as
sound understanding (SU), partial understanding (PU), alternative conception (AC), no understanding (NU),
and no coding (NU) as exposed in Table 1. Conception categorization is carried out to map students'
conceptions with scores that will be analyzed using Rasch analysis. Rasch analysis was carried out to test
validity, reliability and mapping for person and item.
Table 1. Categories and scoring of conceptions
Students’ conceptions Tier 1 Tier 2 Tier 3 Tier 4 Score
Sound understanding (SU) Correct Sure Correct Sure 3
Partial understanding (PU) Correct Sure Correct Not sure 2
Correct Not sure Correct Sure
Correct Not sure Correct Not sure
Correct Sure Incorrect Not sure
Correct Not sure Incorrect Sure
Correct Not sure Incorrect Not sure
Incorrect Sure Correct Not sure
Incorrect Not sure Correct Sure
Incorrect Not sure Correct Not sure
Correct Sure Incorrect Sure
Incorrect Sure Correct Sure
Alternative conception (AC) Incorrect Sure Incorrect Sure 1
No understanding (NU) Incorrect Sure Incorrect Not sure 0
Incorrect Not sure Incorrect Sure
Incorrect Not sure Incorrect Not sure
No coding (NC) If not fill one or more items (tier)
3. RESULTS AND DISCUSSION
The DIGaKiT was developed based on 4D models as follows.

 ISSN: 2089-9823
132
3.1. Defining
On the defining stage, the four-tier test was defined. The four-tier test is a test that consists of four
levels. The first level is multiple choice, the second level is sureness grade for answers at the first level, the
third level is the reason for answers at the first level, and the fourth level is the sureness grade for reasons at
the third level. After that, we have been analyzed material on the kinetic theory of gases for senior high
school students. The data of students’ alternative conceptions on the kinetic theory of gases also collected.
Based on this stage, the DIGaKiT consists of 11 problems namely microscopic and macroscopic properties of
gas (question number 1), the ideal gas assumption (number 2), Boyle's law (question number 3), Gay
Lussac’s law (questions number 4 and 5), Charles's law (question number 6), ideal gas equation (question
number 7), ideal gas pressure (question number 8), ideal gas temperature (question number 9), velocity
average (problem number 10), and energy equipartition theorem (question number 11).
3.2. Designing
At the designing stage, we design the DIGaKiT in a formula of four-tier test. The tier-1 is multiple-
choice for answering the problem. The aim is to identify students' conceptions. The tier-2 is sureness grade
for the tier-1. The aim is to identify students' beliefs about the answers given, whether they are correct and
sure or wrong and sure. The tier-3 is multiple-choice of reasons for the tier-1. The aim is to further identify
students' conceptions as they relate to reasons. Then the tier-4 is sureness grade intended for the tier-3. The
aim is to determine the category of students' conceptions as a whole. The design shown in Figure 4.
Figure 4. Design of DIGaKiT
3.3. Developing
After designing the instrument, we develop 11 questions of the DIGaKiT as shown in Figure 5. At
this stage, we begin to include the question components and options for tier-1 and tier-3. The intended
development is realizing DIGaKiT based on the design that has been prepared in Figure 4.
3.4. Disseminating
After developing process, the DIGaKiT was implemented to 31 students for 60 minutes. Students’
answers at the DIGaKiT were analyzed using categories and scoring in Table 1. The implemented process
was shown in Figure 6. After applying the instrument, we evaluate the instrument created on the Rasch
model. The first result is about the validity of the instrument. The outcome of validity presented in Figure 7.
Figure 7 shows the unidimensionality of the developed instrument. This measure indicates whether the
developed instrument is able to measure what it should measure, and in this case, it is a measure of the
construct of the instrument. The value obtained for “raw variance explained by measures” from DIGaKiT is
55.0% (red box). This result is in the good category because it is above 40% [35]. Then, the outcome of
reliability presented at Figure 8. Based on Figure 8, it can be seen that the result for the Cronbach Alpha of
DIGaKiT is 0.92 which is included in the good category, moreover the value obtained has exceeded the limit
of 0.6 [36]. After that, the distribution of person and item shows at Figure 9.

133
Figure 5. Example of DIGaKiT
Figure 6. Disseminating of DIGaKiT Figure 7. The result of validity grounded on the Rasch model
Figure 8. The result of reliability grounded on the Rasch model
Figure 9 shows the distribution of students' answers to the DIGaKiT. There are two parts shown in
Figure 9 which are separated by the dotted line. The left side is the Person section (purple box) which
contains a student code such as code S22, where S is the code for Student, while 22 is the student's serial
number. To the right is the Item section (pink box) which contains the question code from DIGaKiT such as

 ISSN: 2089-9823
134
code Q1, where Q is the code for Question, and 1 is the serial number of the question. The distribution of
student answers is also largely determined by the scoring in Table 1. The results can be identified that there
are 21 students (green boxes) who have the potential to answer all the DIGaKiT. This is because its position
is above all DIGaKiT questions (blue box). Of the 21 students, the ones with the highest abilities were
students with codes S22 and S25, because their position was at the very top. Meanwhile, there are four
students (red boxes) who potentially cannot answer the DIGaKiT questions. And of the four students, the
student with the lowest ability is the student with code S08. For the quality of the DIGaKiT, questions with
the highest ability to measure students are questions with code Q11, and questions with code Q5 are the
lowest. Moreover, the percentage of students' alternative conceptions shown in Figure 10.
Figure 9. The distribution of person and item based on the Rasch model
Figure 10. The percentages of students’ alternative conceptions

135
From Figure 10, students have alternative conceptions for all questions. The largest percentage of
alternative conceptions is in number 11 (Q11) about the energy equipartition theorem. The smallest
percentage of alternative conceptions is in Q1, Q5 and Q6. The other students’ alternative conceptions were
shown in Table 2.
The DIGaKiT has been developed using the 4D model through the stages of defining, designing,
developing and disseminating. At the end of the stage, the DIGaKiT was analyzed through Rasch model for
validity and reliability. In the Rasch model, an acceptable dimensionality (validity) strongminded via raw
variance explained by measures which ought to be further than 40% [37]. This distribution was also carried
out by several researchers in identifying the distribution of student conceptions or alternative conceptions
[15], [38], [39].
Students’ alternative conceptions on Q11 is “the energy in a gas varies depending on the rate of
reaction of the gas, and energy in a gas depends on the type of gas and does not depend on the temperature of
the gas”. This is likewise one of the explanations why Q11 is the most problematic problem for students to
answer. In accordance with [40], students have an alternative conception of the energy equipartition theorem
“the energy in a gas is contrariwise comparative to the temperature of the gas”. Overall, students have an
alternative conception of the kinetic theory of gas by 19%. This happens because the concept is abstract and
difficult to find in everyday life. Alternative conceptions are the misperceptions that students might have
owing to abstract countryside [13]. Educators will have more trouble in explanation abstract concepts
because there are no physical instances in the everyday existence of the students [41].
In conclusion, students’ alternative conceptions have been analyzed using the DIGaKiT at single of
senior high school in Belitung, Indonesia. The DIGaKiT that in form of the four-tier test was valid and
reliable to practice for analyzed students’ alternative conceptions on the kinetic theory of gases. Educators
must be analyzed students’ alternative conceptions before learning and practice the accurate method to
minimalized alternative conceptions after the learning process.
Table 2. Students’ alternative conceptions on the kinetic theory of gases
No. Sub material Students’ alternative conceptions
1. Microscopic and macroscopic
properties of gases
▪ Macroscopic properties of gas describe the behavior of each gas molecule.
2. The ideal gas assumption ▪ Gas molecules do not meet Newton's laws of motion.
3. Boyle’s law ▪ Pressure and volume relationship graphs for five different gas systems are not sorted
according to the temperature of each system.
▪ A graph of pressure and volume relationship graphs for five different gas systems
starting from the higher system temperature (the deepest curved line) to the lower
system temperature (the outer curved line).
4. Charles’s law ▪ Increased gas temperature causes the air volume to decrease.
▪ Gas volume is contrariwise comparative to gas temperature.
▪ The temperature of the gas does not affect the volume of the gas due to persistent
pressure.
5. Gay-Lussac’s law ▪ Gas temperature is inversely comparative to gas pressure.
▪ There is no change in gas pressure even though the temperature of the gas is
decreasing.
6. Gas pressure in a confined space ▪ The amount of gas pressure in an enclosed space is not influenced by the volume of an
enclosed space.
▪ The quantity of gas pressure is straight comparative toward the volume of closed space.
7. The average effective velocity of
an ideal gas
▪ The effective velocity of the gas is only pretentious thru the molar mass of the gas.
▪ The average effective speed of a gas is only pretentious thru the temperature of the gas.
8. Kinetic energy of ideal gases ▪ Kinetic energy of ideal gases is straight relative to the pressure of the gas so that the
kinetic energy of the temperature is curved upward.
4. CONCLUSION
This research developed DIGaKiT to identify students' alternative conceptions. Based on the Rasch
analysis, it was identified that the level of validity and reliability of the instrument is in a good category. For
validity, it is at a score of 55.0%, which in the Rasch modeling is a good value because it is above 40%.
Reliability is at a value of 0.92. Meanwhile, alternative conceptions of the kinetic theory of gases can be
identified in all questions, and the questions with the highest alternative conceptions are questions with code
Q11 (77%) and the lowest are questions with codes Q1, Q5, and Q6 (4%). Thus, it can be said that the
DIGaKiT can identify conceptual alternatives to the kinetic theory of gases.
ACKNOWLEDGEMENTS
We would like to acknowledge the help of all parties who have supported this research, especially
students and schools where the research was conducted in the Kepulauan Bangka Belitung, Universitas

 ISSN: 2089-9823
136
Pendidikan Indonesia (UPI) and the Directorate of Research, Technology and Community Service (DRTPM),
Ministry of Education, Culture, Research and Technology for funding this research.
REFERENCES
[1] A. Aslan and G. Demircioğlu, “The effect of video-assisted conceptual change texts on 12 th grade students’ alternative
conceptions: the gas concept,” Procedia - Social and Behavioral Sciences, vol. 116, pp. 3115–3119, 2014, doi:
10.1016/j.sbspro.2014.01.718.
[2] Soekarno, B. Csapo, E. Sarimanah, F. I. Dewi, and T. Sabri, “A review of students’ common misconceptions in science and their
diagnostic assessment tools,” Jurnal Pendidikan IPA Indonesia, vol. 8, no. 2, pp. 247–266, 2019, doi: 10.15294/jpii.v8i2.18649.
[3] A. H. Putri, A. Samsudin, M. G. Purwanto, and A. Suhandi, “Examination of conceptual change research over a decade: a
bibliometric analysis using science mapping tool,” Indonesian Journal on Learning and Advanced Education (IJOLAE), vol. 4,
no. 3, pp. 171–190, 2022, doi: 10.23917/ijolae.v4i3.18249.
[4] C. . Wenning, “Dealing more effectively with alternative conceptions in science,” Journal of Physics Teacher Education Online,
vol. 5, no. 1, pp. 11–19, 2008.
[5] M. L. E. Oding, J. A. Palang-at, and A. E. San Jose, “To pass or not to pass: A qualitative inquiry on students’ views on the
academic retention policy,” Journal of Education and Learning (EduLearn), vol. 15, no. 2, pp. 161–167, 2021, doi:
10.11591/edulearn.v15i2.20067.
[6] J. Jumadi, M. I. Sukarelawan, and H. Kuswanto, “An investigation of item bias in the four-tier diagnostic test using Rasch
model,” International Journal of Evaluation and Research in Education, vol. 12, no. 2, pp. 622–629, 2023, doi:
10.11591/ijere.v12i2.22845.
[7] I. Kaniawati, N. J. Fratiwi, A. Danawan, I. Suyana, A. Samsudin, and E. Suhendi, “Analyzing students’ misconceptions about
Newton’s laws through four-tier Newtonian test ( FTNT ),” Journal of Turkish Science Education, vol. 16, no. 1, pp. 110–122,
2019, doi: 10.12973/tused.10269a.
[8] M. Stein, T. G. Larrabee, and C. R. Barman, “A study of common beliefs and misconceptions in physical science,” Journal of
Elementary Science Education, vol. 20, no. 2, pp. 1–11, 2008, doi: 10.1007/bf03173666.
[9] Y. Deringöl, “Misconceptions of primary school students about the subject of fractions,” International Journal of Evaluation and
Research in Education, vol. 8, no. 1, pp. 29–38, 2019, doi: 10.11591/ijere.v8i1.16290.
[10] J. P. Smith, A. A. DiSessa, and J. Roschelle, “Misconceptions reconceived: a constructivist analysis of knowledge in transition,”
Journal of the Learning Sciences, vol. 3, no. 2, pp. 115–163, 1994, doi: 10.1207/s15327809jls0302_1.
[11] S. Waljinah, K. Dimyati, H. J. Prayitno, C. Dwilaksana, A. Rufiah, and E. Purnomo, “The study of euphemism in social media:
Digital technology-based learning media innovation,” International Journal of Innovation, Creativity and Change, vol. 12, no. 2,
pp. 172–184, 2020.
[12] I. Maryati and N. Priatna, “Analysis of statistical misconception in terms of statistical reasoning,” Journal of Physics: Conference
Series, vol. 1013, no. 1, 2018, doi: 10.1088/1742-6596/1013/1/012206.
[13] A. Ilyas and M. Saeed, “Exploring teachers’ understanding about misconceptions of secondary grade chemistry students,”
International Journal for Cross-Disciplinary Subjects in Education, vol. 9, no. 1, pp. 3323–3328, 2018, doi:
10.20533/ijcdse.2042.6364.2018.0444.
[14] H. Eshach, T. C. Lin, and C. C. Tsai, “Misconception of sound and conceptual change: A cross-sectional study on students’
materialistic thinking of sound,” Journal of Research in Science Teaching, 2018, doi: 10.1002/tea.21435.
[15] A. H. Aminudin, I. Kaniawati, E. Suhendi, A. Samsudin, B. Coştu, and R. Adimayuda, “Rasch analysis of multitier open-ended
light-wave instrument (MOLWI): developing and assessing second-years sundanese-scholars alternative conceptions,” Journal for
the Education of Gifted Young Scientists, vol. 7, no. 3, pp. 607–629, Sep. 2019, doi: 10.17478/jegys.574524.
[16] N. J. Fratiwi, T. R. Ramalis, and A. Samsudin, “The three-tier diagnostic instrument: using rasch analysis to develop and assess k-
10 students’ alternative conceptions on force concept,” RSU Conference, no. April, pp. 654–663, 2019, doi:
10.14458/RSU.res.2019.224.
[17] D. Kaltakci-Gurel, A. Eryilmaz, and L. C. McDermott, “Development and application of a four-tier test to assess pre-service
physics teachers’ misconceptions about geometrical optics,” Research in Science and Technological Education, vol. 35, no. 2, pp.
238–260, Apr. 2017, doi: 10.1080/02635143.2017.1310094.
[18] A. Awaludin, H. J. Prayitno, and M. I. Haq, “Using digital media during the COVID-19 pandemic era: good online program in
higher education,” Indonesian Journal on Learning and Advanced Education (IJOLAE), vol. 5, no. 1, pp. 1–12, 2022, doi:
10.23917/ijolae.v5i1.19574.
[19] B. Baker-Eck, R. Bull, and D. Walsh, “Investigative empathy: a strength scale of empathy based on European police
perspectives,” Psychiatry, Psychology and Law, vol. 27, no. 3, pp. 412–427, 2020, doi: 10.1080/13218719.2020.1751333.
[20] J. A. Krosnick and S. Presser, "Question and questionnaire design," in Handbook of Survey Research, San Diego, CA: Elsevier,
2010.
[21] A. Rusilowati, R. Susanti, T. Sulistyaningsing, T. S. N. Asih, E. Fiona, and A. Aryani, “Identify misconception with multiple
choice three tier diagnostik test on newton law material,” Journal of Physics: Conference Series, vol. 1918, no. 5, 2021, doi:
10.1088/1742-6596/1918/5/052058.
[22] M. H. Bassett, “Teaching critical thinking without (much) writing: multiple-choice and metacognition,” Teaching Theology and
Religion, vol. 19, no. 1, pp. 20–40, 2016, doi: 10.1111/teth.12318.
[23] C. Y. Tsui and D. Treagust, “Evaluating secondary students’ scientific reasoning in genetics using a two-tier diagnostic
instrument,” International Journal of Science Education, vol. 32, no. 8, pp. 1073–1098, 2010, doi: 10.1080/09500690902951429.
[24] I. S. Caleon and R. Subramaniam, “Do students know what they know and what they don’t know? using a four-tier diagnostic test
to assess the nature of students’ alternative conceptions,” Research in Science Education, vol. 40, no. 3, pp. 313–337, 2010, doi:
10.1007/s11165-009-9122-4.
[25] D. K. Gurel, A. Eryilmaz, and L. C. McDermott, “A review and comparison of diagnostic instruments to identify students’
misconceptions in science,” Eurasia Journal of Mathematics, Science and Technology Education, 2015, doi:
10.12973/eurasia.2015.1369a.
[26] G. Poutot and B. Blandin, “Exploration of Students’ misconceptions in mechanics using the FCI,” American Journal of
Educational Research, vol. 3, no. 2, pp. 116–120, 2015, doi: 10.12691/education-3-2-2.
[27] G. Liu and N. Fang, “Student misconceptions about force and acceleration in physics and engineering mechanics education,” in

137
International Journal of Engineering Education, 2016, pp. 19–29.
[28] S. Bayraktar, “Misconceptions of Turkish pre-service teachers about force and motion,” International Journal of Science and
Mathematics Education, vol. 7, no. 2, pp. 273–291, 2009, doi: 10.1007/s10763-007-9120-9.
[29] J. Leppavirta, “Assessing undergraduate students’ conceptual understanding and confidence of electromagnetics,” International
Journal of Science and Mathematics Education, vol. 10, no. 5, pp. 1099–1117, 2012, doi: 10.1007/s10763-011-9317-9.
[30] H. Peşman and A. Eryilmaz, “Development of a three-tier test to assess misconceptions about simple electric circuits,” Journal of
Educational Research, vol. 103, no. 3, pp. 208–222, 2010, doi: 10.1080/00220670903383002.
[31] A. C. Prastiwi, A. Kholiq, and W. Setyarsih, “Implementation of ECIRR model based on virtual simulation media to reduce
students’ misconception on kinetic theory of gases,” Journal of Physics: Conference Series, vol. 997, no. 1, 2018, doi:
10.1088/1742-6596/997/1/012034.
[32] L. Wolins, B. D. Wright, and G. Rasch, “Probabilistic models for some intelligence and attainment tests.,” Journal of the
American Statistical Association, vol. 77, no. 377, p. 220, 1982, doi: 10.2307/2287805.
[33] B. Sumintono, “Rasch model measurements as tools in assesment for learning,” in 1st International Conference on Education
Innovation (ICEI 2017), 2018, pp. 38–42. doi: 10.2991/icei-17.2018.11.
[34] N. J. Fratiwi, A. Samsudin, and B. Costu, “Enhancing K-10 students’ conceptions through computer simulations-aided
PDEODE*E (CS-PDEODE*E) on Newton’s laws,” Jurnal Pendidikan IPA Indonesia, vol. 7, no. 2, pp. 214–223, 2018, doi:
10.15294/jpii.v7i2.14229.
[35] D. Adams, B. Sumintono, A. Mohamed, and N. S. M. Noor, “E-learning readiness among students of diverse backgrounds in a
leading Malaysian higher education institution,” Malaysian Journal of Learning and Instruction, vol. 15, no. 2, pp. 227–256,
2018, doi: 10.32890/mjli2018.15.2.9.
[36] S. W. Chan, Z. Ismail, and B. Sumintono, “A Rasch model analysis on secondary students’ statistical reasoning ability in
descriptive statistics,” in Procedia - Social and Behavioral Sciences, Elsevier B.V., 2014, pp. 133–139. doi:
10.1016/j.sbspro.2014.03.658.
[37] S. A. M. Mofreh, M. N. A. Ghafar, A. H. Hj Omar, M. Mosaku, and A. Ma’ruf, “Psychometric properties on lecturers’ beliefs on
teaching function: Rasch model analysis,” International Education Studies, vol. 7, no. 11, pp. 47–55, 2014, doi:
10.5539/ies.v7n11p47.
[38] A. Samsudin et al., “Development of a multitier open-ended work and energy instrument (MOWEI) using Rasch analysis to
identify students’ misconceptions,” Cypriot Journal of Educational Sciences, vol. 16, no. 1, pp. 16–31, 2021, doi:
10.18844/cjes.v16i1.5504.
[39] S. . Ringo, K. Kuswanto, A. Samsudin, and A. Setiawan, “Rural and urban students’ attitudes toward physics: a comparative
study using Rasch analysis,” Journal of Physics: Conference Series, pp. 0–6, 2021, doi: 10.1088/1742-6596/1806/1/012009.
[40] M. N. R. Jauhariyah et al., “The students’ misconceptions profile on chapter gas kinetic theory,” in Journal of Physics:
Conference Series, 2018. doi: 10.1088/1742-6596/997/1/012031.
[41] M. N. R. Jauhariyah, I. Zulfa, Z. Harizah, and W. Setyarsih, “Validity of student’s misconceptions diagnosis on chapter Kinetic
Theory of Gases using three-tier diagnostic test,” Journal of Physics: Conference Series, vol. 1006, 2018, doi: 10.1088/1742-
6596/1006/1/012005.
BIOGRAPHIES OF AUTHORS
Achmad Samsudin is a lecturer at physics education, Universitas Pendidikan
Indonesia, Bandung, Indonesia. His current research interests are the physics education,
science education, cognitive psychology such as identification of conceptions,
misconceptions, conceptual change, development of models, instruments, and media. He can
be contacted at email: achmadsamsudin@upi.edu.
Nurul Azizah is a graduate of physics education, Universitas Pendidikan
Indonesia, Bandung, Indonesia, and a junior high school teacher. Her current research interest
is the development of learning models assisted by digital media to minimize student
misconceptions. She can be contacted at email: nurul_azizah@student.upi.edu.

 ISSN: 2089-9823
138
Nuzulira Janeusse Fratiwi is a graduate of physics education, Universitas
Pendidikan Indonesia, Bandung, Indonesia and an educational practitioner. Her current
research interests are the development of learning models and media to minimize student
misconceptions. She can be contacted at email: nuzulira.janeusse.fratiwi@student.upi.edu.
Andi Suhandi is a lecturer at Physics Education, Universitas Pendidikan
Indonesia, Bandung, Indonesia. He is also a professor at the Universitas Pendidikan Indonesia
in the Field of Physics. His current research interests are the pysics, materials physics, physics
education, science education, and teacing and learning such as conception, misconceptions,
and conceptual change text. He can be contacted at email: andi_sh@upi.edu.
Irwandani Irwandani is a lecturer at Physics Education, Universitas Islam
Negeri Raden Intan Lampung, Lampung, Indonesia. His current research interests are the
education, digital media and learning, physics education, creative thinking, and creativity in
education. He can be contacted at email: irwandani@radenintan.ac.id.
Muhammad Nurtanto is a lecturer at Mechanical Engineering Education,
Universitas Sultan Ageng Tirtayasa, Serang, Banten, Indonesia. His current research interests
are the professional learning, teacher emotion, teacher identity, and philosophy of education.
He can be contacted at email: mnurtanto23@untirta.ac.id.
Muhamad Yusup is a lecturer at Physics Education, Universitas Sriwijaya,
Palembang, Indonesia. His current research interests are the physics education, education,
teacing and learning, and higher order thinking skills. He can be contacted at email:
m_yusup@fkip.unsri.ac.id.

139
Supriyatman Supriyatman is a lecturer at Physics Education, Universitas
Tadulako, Palu, Indonesia. His current research interests are the physics education, education,
teacing and learning, students’ conception, and learning model. He can be contacted at email:
spymfis.untad@gmail.com.
Masrifah Masrifah is a lecturer at Physics Education, Universitas Khairun,
Ternate, Indonesia. Her current research interests are the physics education, education,
TPACK, multirepresentasi, and learning model. She can be contacted at email:
masrifah@student.upi.edu.
Adam Hadiana Aminudin is a lecturer at Electrical Engineering, Universitas
Kebangsaan Republik Indonesia, Bandung, Indonesia. His current research interests are the
physics, development of instrument for identify students’ physics misconception, learning
model, and learning media. He can be contacted at email:
adamhadianaaminudin@mipa.ukri.ac.id.
Bayram Costu is a lecturer at Department of Science Education, Yildiz
Technical University, Istanbul, Turkey. He is also a professor at the Yildiz Technical
University. His current research interests are the teacing and learning, science education,
conception, misconceptions, and conceptual change. He can be contacted at email:
bayramcostu@gmail.com.

Development of DIGaKiT: identifying students’ alternative conceptions by Rasch analysis model

More Related Content

Similar to Development of DIGaKiT: identifying students’ alternative conceptions by Rasch analysis model (20)

More from Journal of Education and Learning (EduLearn) (20)

Recently uploaded (20)

Development of DIGaKiT: identifying students’ alternative conceptions by Rasch analysis model