Reconceptualizing Empirical Data: Developing Higher Order
Thinking Skills in Undergraduate Qualitative Methods Learning
Asep Suryana
a
Department of Sociology, Faculty of Social Sciences, Universitas Negeri Jakarta, Jakarta, Indonesia
Keywords: Competence, Reconceptualization of Empirical Data, Undergraduate Level, Higher Order Thinking.
Abstract: The competence of reconceptualizing empirical data tends to be neglected in the qualitative research learning
system in Sociology Study Programs in Indonesia, especially at the undergraduate level. The author argues
that there are several academic tools that have been pioneered by experts and can be developed into a toolbox
for the competence of reconceptualizing empirical data. However, because the competency of
reconceptualizing empirical data is a high-level reasoning skill, the target competency of reconceptualizing
empirical data is framed so that it can formulate empirical novelty, not theoretical novelty. With the
framework of formulating empirical novelty, the competence of reconceptualizing empirical data requires
undergraduate researchers to be able to thematization and write down their field findings at a more abstract-
conceptual level. For this, sociology students should be skilled at the coding, using the tashawur approach,
and using more theoretical concepts to develop concepts at a more intermediate and grounded level—while
being framed by public issues and current literature as much as the undergraduate student can.
1 INTRODUCTION
Qualitative research skills for sociology graduates are
central. Research competencies for sociology
graduates are the same as drawing skills for
architecture students, or language skills for foreign
language scholars. Therefore, this research skill is
also the main competency of the profile of sociology
graduates (Ferguson & Sweet, 2023; Pike et.al.,
2017), as well as useful as a provision for them to be
ready to enter the job careers (Mekolichick, 2022;
Tambunan and Budiman, 2022).
Overall, the body of knowledge for learning
qualitative research is composed of three patterns.
The first is how to design qualitative research (Flick
[editor], 2022); second, how to collect data (Flick
[editor], 2014); and finally, how to skillfully analyze
data (Flick [editor], 2018). These include
generalization (Maxwell and Chmiel, 2014), coding
(Thornberg and Charmaz, 2014), and theorization
(Kelle, 2014). However, their discussions are aimed
at professional academic researchers, not
undergraduate students. Therefore, the various
terminologies and ideas that surround them must be
adapted to the needs, abilities and learning targets of
undergraduates (Mekolichick, 2022; Tambunan and
Budiman, 2022).
The author argues that the learning outcome of
research at the undergraduate level of sociology is to
formulate empirical novelty—not theoretical novelty.
Theoretical novelty is for PhD level. The empirical
novelty learning outcome is in accordance with the
target of undergraduate education (especially
undergraduate sociology) (Mekolichick, 2022;
Tambunan and Budiman, 2022). In that regard, it is
important to point out that the sociology
undergraduate learning design is patterned after the
vocationalization of sociology. That is, a combination
of the category of policy sociology and the category
of public sociology in the sense of Buraway (2005),
as well as he is directed to have technical skills and
soft skills as preparation for them to enter the enter
the job careers. Even more technically, what is
formulated as reconceptualization of empirical
data—borrowing the typology of data theorization
from Kelle (2014)—is to use more theoretical
concepts to develop derivative concepts at a more
intermediate level and grounded.
The ability to reconceptualize the empirical data
becomes important when we consider strong
complaints about the lack of learning of this
competency in sociology study programs, especially
at the undergraduate level. Swedberg (2012, 2016,
2017), for example, complains about that. The
594
Suryana, A.
Reconceptualizing Empirical Data:Developing Higher Order Thinking Skills in Undergraduate Qualitative Methods Learning.
DOI: 10.5220/0013410600004654
In Proceedings of the 4th International Conference on Humanities Education, Law, and Social Science (ICHELS 2024), pages 594-606
ISBN: 978-989-758-752-8
Copyright © 2025 by Paper published under CC license (CC BY-NC-ND 4.0)
capacity to theorize and conceptualize various great
figures of sociology (such as Bourdieu) ms to be
obtained naturally, not because of formal education
in college.
The neglect of learning on the competence of
reconceptualizing empirical data also occurs in
Indonesian universities. If we look at the syllabus of
lectures and textbooks of qualitative research in
Indonesian at the undergraduate level, the ability to
reconceptualize empirical data is not considered
important. The discussion of lecture syllabi and
textbooks of qualitative methods in Indonesian tends
to focus on ontological aspects (what to look for in
qualitative research) and how data collection
techniques—and is always contrasted with
quantitative research (Moleong, 2019; Mulyana,
2010).
To discuss the empirical data reconceptualization
competency argument, this article is divided into five
sections. The first part is to place the competence of
reconceptualizing empirical data in the realm of data
analysis and at the level of higher order thinking. The
reconceptualization goal is to formulate empirical
novelty at a more intermediate level. The second part
is a description of the research method that
emphasizes literature study. There are various types
of literature tracked in this article. The third and
fourth sections discuss the body of knowledge of
reconceptualizing empirical data and learning
outcomes of undergraduate qualitative research. The
last section discusses various academic tools that can
be used to develop competence in reconceptualizing
empirical data.
2 THEORETICAL FRAMEWORK
This article uses the learning outcomes approach. As
a pedagogical strategy that places students at the
center of learning, the learning outcome approach
aims to build specific competencies (both at the level
of technical skills and soft skills) that students have
after taking a course (Zlatkin-Troitschanskaia et.al.
(editors), 2018; Arnold et.al. (editors), 2020). In this
context, the learning outcome of data
reconceptualization competency is being able to
construct and formulate empirical research findings.
The competency of reconceptualizing empirical
data is a technical academic skill that undergraduate
students should have, albeit in a basic level form. It is
a sub-competency of the qualitative researcher
competency. Of course, there is a limit to the
achievement of empirical data reconceptualization
competencies when taught at the undergraduate level.
From the author's experience teaching in the
Sociology Study Program for 27 years (1997-2024)
(Suryana, 2012), the target competency of
reconceptualizing empirical data is for undergraduate
students to be able to formulate empirical novelty, not
theoretical novelty. The target of theoretical novelty
is not realistically taught at the undergraduate level
because it is the main competency of the doctoral
level.
Empirical novelty means that undergraduate
researchers can thematization and write down their
field findings at a more abstract-conceptual level. Of
course, the conceptualization process is guided by the
underlying central theory/concept—while being
framed by public issues and current literature to the
best of the student's ability (Orange, 2023; Dodgson,
2019). At the same time, in order to reconceptualize
empirical data, undergraduate students must also be
able to record and reconstruct data (write fieldnotes,
write diaries, and write memos), and be able to
analyze data (open coding of fieldnotes, visualization
of initial field findings, thematization of field
findings, design of chapters and subchapters, writing
reports, and linking empirical data findings with
related literature) (Figure 1).
On the other hand, as a pedagogical strategy, the
learning outcomes approach is also related to the
body of knowledge in the field of science being
taught. If the body of knowledge contains a map of
information, concepts, theories or rules in a field of
science, learning outcomes are more specific.
Learning outcomes aim to define the
various
elements of the field's body of knowledge that
students must master (Miles & Wilson, 2004). Body
of knowledge provides raw material for formulating
learning outcomes. Meanwhile, learning outcomes
are formulated from the concepts, rules, and
competencies in the body of knowledge.
In other words, the body of knowledge is the
foundation for the formulation of learning outcomes.
The formulation of learning outcomes should be
based on the structure and content of the body of
knowledge of a field of study (Thorn & Sydenham,
2008). A good body of knowledge can serve as a
guide, foundation and reference for which parts of the
body of knowledge are important to be mastered by
learners and formulated as learning outcomes.
Reconceptualizing Empirical Data:Developing Higher Order Thinking Skills in Undergraduate Qualitative Methods Learning
595
Figure 1: Body of Knowledge Reconceptualizing Empirical Data.
So, not everything in the body of knowledge is
learned. Learning outcomes emphasize, limit, and
direct only the relevant and urgent parts of the body
of knowledge to be learned. Furthermore, learning
outcomes that are well formulated will help learners
connect the knowledge they gain with real situations
in everyday life.
3 RESEARCH METHODS
As research categorized as teaching and learning in
Sociology, this article takes three methodical steps to
collect and compile empirical data
reconceptualization competencies.
First, this research explores five types of literature
to identify various academic techniques and tools that
have previously been pioneered by experts, to
formulate them as academic tools to build
competence in reconceptualizing empirical data.
(1) Teaching and learning in sociology literature,
especially those related to qualitative research
learning strategies such as Medley-Rath (2023); as
well as those related to building critical reasoning
skills in sociology (Kane & Otto, 2017; Kane, 2023).
(2) The qualitative methodology literature itself as
indicated by Babbie 2021; Cresswell (2016),
Newman 2014), Mills & Hubermans (2014), and
Morse (2006). (3) The theorized competence
literature of Swedberg (2012, 2016, 2017) and Kelle
(2014). (4) Literature of Mantiq (Islamic Logic)
textbooks, especially related to the tashawur
(conception) approach (Sambas, 1996 [2017]: 46-68;
Muminin, 2022; Al-Abhari, 2022; Nuruddin, 2020;
Hurley & Watson, 2018; Hayon, 2000). (5)
Teaching and learning social research methods
literature (Nind [editor], 2023).
Second, this research attempts to build on the
academic tools previously pioneered by Swedberg
(2017, 2016, 2012). Following Swedberg (2017,
2016, 2012), this research argues that the competence
of reconceptualizing empirical data is carried out in
two stages: (a) the context of justification and (b) the
context of discovery. The context of justification is to
describe how theory is practiced in research. Whereas
the context of discovery is where relevant academic
tools are used to gain insights, and then the theory
used in the context of justification stage is further
developed (Burawoy, 2009).
The various academic tools extracted from the five
types of literature are grouped into two stages or ideal
types—following the stages of Swedberg (2017, 2016,
2012)—namely (a) the context of justification and (b)
the context of discovery. The author argues that the
various academic tools of qualitative research learning
strategies obtained from the repertoire of teaching and
learning in sociology and qualitative methodology
literature are in the context of justification. These
academic tools are the skills of collecting and
processing, visualizing data along with how the
conceptual framework used can function as a frame
and guide for collecting, processing, and visualizing
empirical data.
Meanwhile, the theorized academic tools of
Swedberg (2012, 2016, 2017) and Kelle (2014), the
higher-level thinking and critical sociological
thinking competencies of Kane & Otto (2017) (Kane
2023), and various academic tools from Mantiq (such
as tashawur, division, classification, and predicable)
can be formulated as an academic toolbox for the
discovery context.
In this regard, the author tries to operationalize (a)
ICHELS 2024 - The International Conference on Humanities Education, Law, and Social Science
596
the context of justification and (b) the context of
discovery as formulated by Suryana (2020).
Following Swedberg's (2017, 2016, 2012), the
process of reconceptualizing empirical data begins
with the identification of insights, because they are
not covered by the main theory or auxiliary theory
used (Buroway, 2009). The insights are then further
developed, to provide a contribution of elements of
conceptual for the development of the theoretical
approach used (Suryana, 2020).
The third step is to reflect on the stages of learning
Qualitative Research Practices (PPK) that have been
held by the Sociology Study Program and the
Sociology Education Study Program at the
Universitas Negeri Jakarta for 18 years, from 2006 to
2024. It should be stated that the Sociology Study
Program and the Sociology Education Study Program
have organized Qualitative Research Practices in a
guided manner since 2006, which is a continuation of
the Qualitative Research Methods course. If the
theoretical aspects are taught in the Qualitative
Research Methods course, the practical aspects are
carried out in Qualitative Research Practice. Of
course, during the 18 years of learning Qualitative
Research Practice, various learning instruments have
been innovated and institutionalized, and some of the
learning outcomes of Qualitative Research Practice
have been recorded by Suryana (2012).
This research tries to complement Suryana's
(2012) article, especially in terms of data
reconceptualization competence. The focus of this
research is on the learning stages that allow data
reconceptualization competencies in Qualitative
Research Practice to be honed and built. The focus
of data collection is on the phases of writing
fieldnotes, visualizing field findings, writing memos,
thematizing findings, drafting chapters and
subchapters, writing reports, and linking empirical
data findings with related literature. The learning
stages of Qualitative Research Practice that have been
institutionalized for 18 years (2006-2024) can be used
as a source of field data, as well as a reference for
reflection to build the competence of
reconceptualizing the empirical data that is the focus
of this research.
3.1 Body of Knowledge
Reconceptualizing Empirical Data
Where is the position of data reconceptualization
competency in the body of knowledge of qualitative
research. Following Flick's categorization (2014, 2018,
and 2022), the competency of reconceptualizing
empirical data is in the realm of data analysis. There
are two directions of data reconceptualization, namely
from the angle of warrant, and the angle of the
relationship between the theory/concept and the
empirical data itself (Babbie, 2021: 29-59). Figure 1
shows three guidelines for competence in
reconceptualizing data from the warrant angle. The
suffix [re] in conceptualization indicates these three
things. They are the central theory or concept used, the
public issue framing it, and the state of the art of the
recent literature examine.
Meanwhile, in terms of the relationship between
theory/concept and empirical data, the
reconceptualization of empirical data is developed
from Kelle's (2014) three typologies of data
theorization. The first typology is (1) using more
theoretical concepts to develop concepts at a more
intermediate level. (2) Putting qualitative data as
material to revise more theoretical concepts. Finally
(3) is to transfer the intermediate concepts to a new
research domain. For the understanding of
reconceptualizing empirical data at the undergraduate
level of sociology, it refers to the first typology. That
is, using more theoretical concepts to develop
concepts at a more intermediate level and grounded
(Babbie, 2021).
Figure 1 shows the body of knowledge for
reconceptualizing empirical data as a set of technical
skills for qualitative research academics. It starts with
the skill of collecting and recording empirical data to
writing a report. The first step in reconceptualizing is
to be able to write fieldnotes and memos.
Fieldnote (FN) is (a) a medium for recording field
data, as well as (b) a material for processing data at an
advanced stage. As a field data recording medium, the
FN contains emic data (in the form of ideas, issues,
sentences, etc. from informants), what was observed,
and what was heard. Meanwhile, as material for
processing data at an advanced stage, FN also contains
the researcher's comments or (ethical) analysis; and (ii)
the grouping, classification and categorization of data
through open coding.
The memo writing is done after writing the FN.
Writing memos is done after several open codes have
been grouped into axial codes. Memo is a detailed
description of axial coding. After the axial-coding is
found, to detail or illustrate the axial-coding, a memo
is written.
So, a memo is a conceptualization of data. It does
not simply report data. A memo (1) must be able to tie
together disparate pieces of data and formulate them
into a unified group. It can also contain (2) fragments
of data that are assembled as examples, illustrations, or
evidence of more abstract concepts. Memos are titled
(with the key concept discussed). Similar memos are
Reconceptualizing Empirical Data:Developing Higher Order Thinking Skills in Undergraduate Qualitative Methods Learning
597
filed under the same theme or umbrella concept; and
separated from the data archive. Thus, memos should
contain the results of axial coding and have moved in
a more conceptual direction.
Composing FNs and memos requires technical
writing skills. For FNs, it requires descriptive and
narrative writing skills. As for composing memos, it
requires higher technical skills—in Marahimin's
(2000) terminology—referred to as expository
writing techniques.
Writing a description is describing an object,
place, atmosphere, or situation with words in a lively
and captivating manner. Through his writing, the
reader .ms to be able to. what the author’s, "taste"
what the author eats, "feel" what he feels, and
"conclude" what the author concludes (Marahimin,
2000). The content of descriptive writing is the result
of what is observed, what is heard, and what is felt
through all five senses that the author has in a certain
place and time.
Narrative is writing down the events or characters
that are being told. Narrative writing has a plot (a story
that has a flow) and has a focus, claim, angle,
argument, controlling idea, or thesis. Marahimin
(2000) mentions other characteristics of narrative
writing. Among them are (1) plot: events, characters,
and conflicts; (2) setting (time setting, place setting,
economic setting, cultural setting, political setting,
government setting, social setting) or local setting. (3)
Point of view, writing angle, or narrator's position (I-
ness; or he-ness). (4) Dialogue, and (4) narrative
pattern (flashback style; beginning-middle-end).
Meanwhile, expository writing techniques are very
helpful for writing memos. Expository writing is
writing that contains proof of a thesis, claim, or
controlling idea. In memos, the thesis that the writer
wants to put forward is embodied in the title. The
whole description is about proving that the title is true.
3.2 Qualitative Research Learning
Outcomes for Undergraduate
Program
This article argues that the target competency of
reconceptualizing empirical data is for undergraduate
students to formulate empirical novelty, not
theoretical novelty. The target of theoretical novelty
is not realistic to be taught at the undergraduate level
because it is the main competency of the doctoral
level. In that context, the competency of
reconceptualizing empirical data of qualitative
research is based on two things. First, (1) students'
ability to categorize and systematize their empirical
data to a more abstract-conceptual level, and (2) their
ability to draft chapters and subchapters (Table 1, and
Figure 1).
In order for the first competency to be achieved,
there are three supporting skills that must be mastered
by prospective sociology graduates. The three are (a)
being able to record and reconstruct data (writing
fieldnotes, writing diaries, and writing memos); (b)
being able to perform three stages of coding (open
coding on fieldnotes, axial coding, and selective
coding); and (c) being able to visualize research
findings (tables, matrices, flowcharts, concept
mapping) (Newman, 2014; Hubermans and Marshal,
2014; Thornberg and Charmaz, 2014).
Meanwhile, the competency of organizing the
chapter design is divided into three sub competencies
(Table 1). In order to be able to write relevant
headings or terminology, students are trained to be
able to tie the description with a title that has the
characteristics of: (a) describes what is in the content
of the description, (b) is interesting (eye catching), (c)
readers feel the need to read, (d) contains a maximum
of 12 words, and (e) is written in the form of phrases,
not sentences. The title should not only be conceptual
but should be written in the form of a concept that
already has a variety of values or “variables”.
On the other hand, the skill of composing the title
should reflect specific keywords or terminology that
are guided and based on the central theories/concepts
used. Students must also be able to dialectic their
conceptual guidance with the empirical data findings
(Wagner, 2009). The results of the dialectic are then
categorized, thematized, and visualized by framing
them on their theoretical foundation (Morse, 2006;
Kane & Otto, 2017). In fact, the dialectic is already in
the category of synthesis, because it tries to interrelate
the theoretical foundations he has with the tendencies
and reasoning of the empirical data he encounters
(Dodgson, 2019). This process is a more advanced
stage of higher order thinking.
The above synthesis process is also rooted in the
sociological research tradition itself. The research
methods literature in sociology often emphasizes that
the categorization, thematization and visualization of
research findings should be consistent with the
paradigmatic position of sociology that the researcher
takes (Marvasti 2004; Wagnera, Garner and
Kawulichc, 2011). Indeed, as a multi-paradigmatic
science (Ritzer 1975; Purdue 1986), the discipline of
sociology demands that qualitative research
conducted by a researcher must be in line with the key
ideas of the overarching sociological paradigm
(Babbie 2021). Reconceptualization of empirical data
must also be guided and in line with the overarching
sociological paradigm.
ICHELS 2024 - The International Conference on Humanities Education, Law, and Social Science
598
Table 1: Learning Outcomes of Competency in Reconceptualizing Empirical Data for Undergraduate Programs.
Sub-Competencies Sub-Competency Elements
(1) Undergraduate students can classify, categorize,
and thematize empirical data to a more abstract
conceptual level.
(1) Can record and reconstruct data (writing
fieldnotes, diary writing, and memo writing)
(2) Can perform three stages of coding (open
coding on fieldnotes, axial coding, and selective
coding)
(3) Can visualize research findings (tables,
matrices, flowcharts, concept mapping)
(2) Be able to draft the organization of chapters and
subchapters
(1) Write down relevant headings or terminology
(2) The keywords and terminology are guided and
based on the central theories/concepts used.
(3) The chapters and subchapters are framed and
guided by:
(a) the public issues surrounding it.
(b) the latest literature to the best of the
undergraduate student's ability.
(c) the reasoning of the approach/theory/concept
used.
The key words and derivative terminology above
reflect how theory is used and operationalized
(deductively) for a particular topic, research subject
and research location. Using Kelle's (2014) typology
of theorizing, this higher stage of reasoning is using
more theoretical concepts to develop concepts at a
more intermediate and grounded level. At this stage,
inductive reasoning is more dominant. The more
abstract theoretical concepts are only placed as
framing. The deductively derived key terms serve as
a frame: so that the process of coding, inductive
reasoning, or conceptualization can be carried out.
From that angle, the prospective sociology scholar
should be able to transfer and operationalize the
concepts he uses to the topic and location of his
research. And at the same time, the formulation of
derivative terms is also to place qualitative data as
material for revising and modifying these more
theoretical concepts (Kelle, 2014).
The headings and subheadings are then organized
into a chapter and subchapter layout. It is like the
table of contents in a book. The chapters should
reflect the reasoning framed by the theory used. It
should also reflect the author's response to current
public issues and literature to the best of the
undergraduate student's ability.
In this regard, various writing development
techniques found in textbooks can be referred to.
Choesin (2016) and Bailey (2003, 2018), for
example, have shown how a piece of writing is
developed. Some are chronological, flashback,
effect-to-cause, per-aspect, and others. The pattern of
writing development as proposed by Choesin (2016)
and Bailey (2003, 2018) can be referred to and
developed for writing report chapters. Students can
combine two or even three flows for the writing
division.
However, the reconceptualization competencies
in Table 1 must be based on more general
competencies that qualitative research learners must
master. First, qualitative learners must learn to
formulate research problems in qualitative research
(Table 2). Crasswell (2014) recommends that
qualitative research problems be formulated as a
single phenomenon.
Furthermore, the formulation of research
problems is narrowed down into research questions
(Table 2). The style of the formulation can take the
form of (1) the existence of problems, issues,
difficulties, dilemmas, gaps, or obstacles between
what should be (das sollen) and what happens (das
sein). The gap in question can occur in everyday life,
literature, or theory, or in practice. The issue shows
the need to be researched. (2) The formulation style
is based on curiosity.
Reconceptualizing Empirical Data:Developing Higher Order Thinking Skills in Undergraduate Qualitative Methods Learning
599
Tabel 2: Supporting Competencies for Reconceptualizing Empirical Data in the Undergraduate Program.
(1) Formulate the research problem precisely
(1) Can formulate research problems from the
right angle.
(2) Framed and guided by:
(a) Underlying
centr
al theory/concept
(b) Public issues
(c) Up-to-date literature to the best
of the undergraduate student's
ability.
(3) Can formulate typical qualitative research
questions guided by underlying central
theories/conce
p
ts.
(2) Operationalize and use central concepts, theories, or
sociological approach appropriately
(3) Writing a research report
It can relate empirical data findings to related literature.
3.3 Academic Tools Competency
Reconceptualization of Empirical
Data
3.3.1 The Three Stages of Coding and
Visualization of Findings
In a number of qualitative research textbooks (for
example Babbie (2021) and Newman (2014)), coding
is the main technique of qualitative data analysis. The
results of the coding are then visualized in the form
of tables, figures, diagrams, and so on. This coding
technique is adopted from the grounded research
approach in qualitative research.
Coding is assigning marks (codes) to field data. In
some qualitative methods textbooks such as Babbie
(2021) and Newman (2014), coding is the assignment
of terms (keywords, single words, or phrases) to mark
empirical phenomena. Here, first, the coding
technique contains a categorization or grouping
strategy: which phenomena are the same or similar,
and which phenomena are different. Similar
phenomena are then grouped together and given a
code (a specific term).
Second, as a keyword technique, coding is done
in stages, towards the more abstract. Thus, coding
moves from empirical phenomena to more abstract-
conceptual ones. In this regard, the three stages of
coding as proposed by Babbie (2021) and Newman
(2014) can be used. They are open coding, axial
coding, and selective coding (Figure 2).
Open coding is the first step in analyzing
empirical data. Each empirical phenomenon that is
deemed important is given a name or term. Here, the
question arises as to how to establish that one
phenomenon is important, and another is not. In this
regard, the central theory or concept used plays a
significant role. Through the procedure of
operationalizing the theory or central concept, the
researcher will have sensitivity and could judge
whether an empirical phenomenon is important or
not. Therefore, in the open coding stage, the skill of
operationalizing theories or concepts is important to
master.
In the language of Toulmin (1959, 1983, 2003)
and Booth (2008), the capacity of the theory that has
been operationalized and functions as a determinant
of data or phenomena is called a warrant. Warrant
works as a rule that guides, frames, and sorts out
which data is considered important. The
operationalized theory acts as a warrant.
The skill of using and operationalizing the
theories and concepts so that they work as warrants,
will also guide in choosing specific terminology in
giving names to data and phenomena that are
considered important. Terminology must be an
implication of the theory both in terms of reasoning
and the terms themselves.
Furthermore, in this step of coding at a higher and
more abstract level, the guidance of theory as a
warrant is even more important. In addition to the
theory-based reasoning of terminology, the choice of
diction must also correspond to the key words or
concepts that underpin the theory.
ICHELS 2024 - The International Conference on Humanities Education, Law, and Social Science
600
Figure 2: Three levels of coding.
At an advanced stage, a few open coding that have
similarities are regrouped into one coding. This stage
is called axial coding, categorization based on the
same axis (theme). Finally, selective coding, a single
phenomenon that encompasses all aspects, themes, or
mechanisms found (. also Cresswell, 2014).
It is also important to master connectivity
strategies between categories (at least at the axial
coding level)—as suggested by Maxwell and Chmiel
(2014a). The connectivity strategy is to explore the
mechanisms that connect axial coding, such as
looking for intertwining or causal mechanisms (.
Maxwell and Chmiel 2014a). In fact, to make
connectivity easy to construct and communicate,
undergraduate students need to master the technique
of visualizing findings in the form of tables,
diagrams, matrices and so on (Mills and Hubermans,
2014).
3.3.2 The Tashawur Approach in Developing
Terminology or Coding
Tashawur is one of the academic skills in Mantiq. In
general, Mantiq is a science that has developed in the
Muslim world since the Middle Ages and was
developed from Greek Logic, but it has its own
characteristics. One of the features of Mantiq that is
relevant to this focus is the tashawur material.
Tashawur is an academic skill to organize the term
(lafadz) and the intention, understanding, meaning of
the term precisely. The precision of the meaning he
refers to by giving the term precisely is the object of
study in tashawur (. Sambas, 1996 [2017]:46-68;
Muminin, 2022; Al-Abhari, 2022; Nuruddin, 2020).
In this material on tashawur, learners become
more sensitive to words or word combinations with
the meanings they refer to. In that case, the tashawur
approach emphasizes (1) the mastery of term both
single term and composed along with the meaning or
understanding it refers to. Likewise, (2) the level of
abstraction of the term is highly emphasized in this
tashawur approach. Whether the term is at a high
level of abstraction, so that it must capture its
meaning through thought (such as the term
democracy). or the level of abstraction is low (such as
the word house). The term house can be understood
through the senses.
Examples of singular and composed terms are
house (singular term), hospital (two-word- phrase
term), or Cipto Mangunkusuomo hospital (three
words referring to one particular hospital). Even if the
term or word is only one, the intended meaning is a
single sense or thing. Also, even though the
compound Cipto Mangunkusomo Hospital consists
of three words, the phrase refers to a hospital on Jalan
Salemba in Central Jakarta.
Another typology of terms or terminology that is
important to master in the tashawur approach is
whether the term is universal or particular. The word
human is a universal term, referring to a general
figure. But President Prabowo Subianto is a specific
term. It refers to a person who is currently (2024-
2029) the president of the Republic of Indonesia.
It is also important for the competent person to
provide definitions for the terms formulate, so that
others can understand what they mean. One type of
definition that is relevant to the competence of
reconceptualizing empirical data is the essential (or
predicable) definition. An essential definition is an
answer to the question of what is (e.g. what is a
human being). Students should be able to answer that
question using five predicable terms (or kulliyatu al-
khomsah—Arabic).
Competence in taqsim (dividing) is also
important. Taqsim is the ability to trace the elements
of a terma (a word or combination of words). For
example, about a house. Taqsim answers what are the
elements of a house, or how the term house is
categorized.
So, this taqsim competency is important, because
Reconceptualizing Empirical Data:Developing Higher Order Thinking Skills in Undergraduate Qualitative Methods Learning
601
it enables the scholar to categorize words. He can
specify the elements of a word, or the further
categories of a term. They can show that a few words
are connected because they have an upper, more
abstract word that can overshadow other words below
it.
So, there are three competencies from the
tashawur approach that can be integrated with the
three levels of coding, namely (1) typology of terms
(lafadz), (2) essential definitions-predicable
(kulliyatul khomsah), and (3) taqsim (division). The
three components of tashawur can enhance the
mastery of key terms, the meanings they refer to, and
the tinkering with words, terms, or concepts. The
tashawur approach allows undergraduate researchers
to thematize and formulate their field findings into a
more abstract conceptual level, through a three-level
coding approach aided by the tashawur approach.
3.3.3 Deduction, Induction, and Abduction
Reasoning
Deductive, inductive and abductive reasoning are the
three patterns of reasoning underlying qualitative
research. They are used in specific proportions and
are different from the proportions and composition of
their use in quantitative research. Even within
qualitative research itself, the proportion of each of
the three reasoning patterns used varies during the
research design stage (Thornberg, 2022), during data
collection (Kennedy and Thornberg, 2018), and
during data analysis (Reichertz, 2014).
Deduction reasoning is the first step in
reconceptualizing empirical data. Deductive
reasoning serves as a guide (warrant, sensitizing)
(Booth et.al., 2008) and how abstract reasoning or
concepts are operationalized to the empirical level (in
the form of indicators or parameters; Babbie, 2021).
At the research design stage, this deductive reasoning
guides the research angle, formulates the research,
and guides the research questions (even the key
concepts in the theory we use are explicit in the
formulation of research questions). The central theory
or concept that has been operationalized to the
empirical level (indicator or parameter) also becomes
a reference in collecting data to analyzing data and
writing reports. The use of deductive reasoning in
1
The author uses the term working hypothesis (which is
widely used in qualitative research) instead of the term test
hypothesis. The main difference between the two types of
hypotheses is the use of theory. In a test hypothesis, the
domain is deductive reasoning, and the aim is to prove the
theory. Whether the field data is in accordance with the
theory or even contradicts the theoretical reasoning. The
qualitative research is relatively minimal. It is not as
strong as quantitative research.
Furthermore, this deductive reasoning becomes
the main ingredient of abductive reasoning. In simple
terms, abductive reasoning can be understood from
three angles. (1) The deductive dimension means
operationalizing the theory into a few working
hypotheses.
1
The best working hypothesis is selected
and used. The less appropriate working hypothesis is
put away first, maybe it will be used later. So,
abduction reasoning is the use of the most appropriate
working hypothesis, serving as a research guide, and
the working hypothesis is shifted and changed
according to the data findings. Here, abduction
reasoning relies on the operationalization of theory
from deduction reasoning.
In the abduction reasoning, there is an element of
looking for "potential suspects". The hypothesis
becomes the focus and guide to find evidence or data
so that the "suspect" becomes the "defendant".
Furthermore, the data is collected, so that it becomes
evidence and the defendant. However, once the
complete data has been fulfilled, the third principle,
namely retroduction, applies.
(2) Retroduction is the back-and-forth
principle. It connects the hypothesis as the initial
idea (which ks potential suspects) with empirical
data. The hypothesis work serves as a guide to find
data that will serve as proof. However, it is possible
that the data collected is different and even
contradicts the working hypothesis. In that case, the
working hypotheses are shifted or even changed. It is
possible that several hypotheses that were previously
stored are then chosen again to become working
hypotheses because they are in accordance with field
data. Then a working hypothesis is taken from the
working hypothesis bank and becomes a replacement
for the original working hypothesis. If it does not
exist, appropriate concepts or theories are sought.
If a central theory or concept that is relevant and
overshadows the field data findings is obtained, and
has been operationalized into a working hypothesis,
then the working hypothesis is used as a claim or
thesis. In addition to the change in position from
working hypothesis to claim (thesis), the claim also
serves to overshadow the field findings. Field
findings are the proof of the thesis. The fidelity to
result is theory verification, theory rejection, or theory
modification. In contrast, working hypotheses function as
warrant or sensitizing. The working hypothesis becomes a
guide in collecting and analyzing data. Once the data
obtained is different from the working hypothesis, let alone
contradictory, then the working hypothesis is changed, and
adjusted to the field findings.
ICHELS 2024 - The International Conference on Humanities Education, Law, and Social Science
602
Interpretation of
Level 3
Interpretation of
Level 2
Interpretati
on of
Level 1
Adapted from Wuisman 2024:6.
Figure 3: Inductive and Deductive Reasoning Patterns.
data findings and the back and forth principle of the
relationship between theory (working hypothesis)
and field data is referred to as the principle of
retroduction (Downdie, 2019).
Inductive reasoning, on the other hand, is the
opposite of the deductive pattern (Figure 3). Inductive
reasoning is a pattern of reasoning that draws
abstractions from empirical phenomena into
conceptual-abstract things. There are three forms of
this induction strategy. The first is the generalization
strategy (Kennedy & Thornberg, 2018) or also
referred to as the categorization strategy (Maxwell
and Chmiel, 2014a), or what in this article is referred
to as coding. Thornberg and Charmaz, 2014). Second,
is the strategy of connecting between these categories
as discussed in the coding section (Maxwell and
Chmiel, 2014a),
The third strategy is to explore emic
interpretations and then frame them ethically (Willig,
2014). Various results of emic categorization
(especially in the open coding stage) are framed and
grouped from the point of view of the theory used
(Wuisman, 2024). Here, theory serves as a guide for
categorization or thematization of coding. This stage
of analysis was carried out at the axial coding level.
The results of this three-level coding process produce
categorizations, themes, or mechanisms that are more
abstract, conceptual, and in accordance with the
central concept or theory used.
The author uses the term working hypothesis
(which is widely used in qualitative research) instead
of the term test hypothesis. The main difference
between the two types of hypotheses is the use of
theory. In a test hypothesis, the domain is deductive
reasoning, and the aim is to prove the theory. Whether
the field data is in accordance with the theory or even
contradicts the theoretical reasoning. The result is
theory verification, theory rejection, or theory
modification. In contrast, working hypotheses
function as warrant or sensitizing. The working
hypothesis becomes a guide in collecting and
analyzing data. Once the data obtained is different
from the working hypothesis, let alone contradictory,
then the working hypothesis is changed, and adjusted
to the field findings.
4 CONCLUSION
From a pedagogical point of view, the ability to
reconceptualize empirical data is categorized as
higher order thinking. Students not only record and
record empirical data. In fact, he must be able to
dialectic the conceptual guidelines he has with his
empirical data findings. The results of the dialectic
are then categorized, thematized, and visualized by
framing them on their theoretical foundation. In fact,
Classification system, name, category,
type
Basic conceptual framework
Dimensions and key concepts
Conceptualization- Abstraction
Operationalization of the concept
Participant/subject understanding
meaningful signs
Reconceptualizing Empirical Data:Developing Higher Order Thinking Skills in Undergraduate Qualitative Methods Learning
603
dialectic is already in the category of synthesis,
because it tries to interrelate the theoretical
foundations he has with the tendencies and reasoning
of the empirical data he encounters.
The above synthesis process is also rooted in the
sociological research tradition itself. The research
methods literature in sociology often emphasizes that
the categorization, thematization and visualization of
research findings should be consistent with the
paradigmatic position of sociology. Indeed, as a
multi-paradigmatic science, the discipline of
sociology demands that the qualitative research
conducted by a researcher must be in line with the
key ideas of the overarching sociological paradigm.
Reconceptualization of empirical data must also be
guided and in line with the overarching sociological
paradigm.
REFERENCES
Al-Abhari, Sheikh Atsirudin, 2020 [no year]. Kitab
Ishaghuji. Translation of Abi Kafa Bihi HSB.
Mukjizat.
Arnold, Christine et.al. (Editors), 2020. Learning
Outcomes, Academic Credit, and Student Mobility.
Montréal & Kingston: Queen's University McGill-
Queen's University Press.
Atkinson, Maxine P and Kathleen S Lowney, 2016. In
Trenches: Teaching and Learning Sociology. New York:
W.W. Norton.
Babbie, Earl, 2021. The Practice of Social Research.
Fifteenth Edition. Boston: Cengage.
Burawoy, Michael, 2005, For Public Sociology.
American Sociological Review 70: 4. Doi:
10.1177/000312240507000102.
Burawoy, Michael, 2009. The Extended Case Method: Four
Countries, Four Decades, Four Great Transformations
and One Theoretical Tradition. Berkeley: University of
California Press.
Cabrera, Sergio A & Stephen Sweet (Editors), 2023.
Handbook of Teaching and Learning in Sociology.
Glethenham: Edward Edgard Publishing.
Cannella, Gaile S, 2022. Ethical Entanglements:
Conceptualizing 'Research Purposes/Design in the
Contemporary Political World'. In Uwe Flick (Editor).
The Sage Handbook of Qualitative Research Design.
London & Thousand Oaks: Sage Publications.
Copi, Irving M; Carl Cohen, and Victor Rodych, 2019
[1953]. Introduction to Logic. Fifteenth Edition. New
York: Routledge.
Creswell, John W., 2016. 30 Essential Skills for the
Qualitative Researcher. Thousand Oaks Road,
California: Sage Publications.
Creswell, John W. & Cheryl N. Poth, 2018. Qualitative
Inquiry & Research Design: Choosing Among Five
Approaches. Fourth Edition. Thousand Oaks,
California: Sage Publications Ltd.
Creswell, John W. & J. David Creswell, 2018. Research
Design Qualitative, Quantitative, and Mixed Methods
Approaches. Fifth Edition. London: Sage.
Denzin, Norman K., 2014. Writing and/as Analysis or
Performing the World. In Uwe Flick (Editor). The Sage
Handbook of Qualitative Data Analysis. London &
Thousand Oaks: Sage Publications.
Dodgson, Joan E., 2019. Reflexivity in Qualitative
Research. Journal of Human Lactation 1-3. DOI:
10.1177/0890334419830990.
Ferguson, Susan J. and Stephen Sweet, 2023. The Core: The
Sociological Literacy Framework. In Sergio A. Cabrera
& Stephen Sweet. Handbook of Teaching and Learning
in Sociology. Glethenham: Edward Edgard Publishing.
Gob, Giampietro, 2008. Re-conceptualizing
Generalization: Old Issues in a New Frame. In Pertti
Alasuutari, Leonard Bickman, & Julia Brannen. The
Sage Handbook of Social Research Methods. London
& Thousand Oaks: Sage Publications.
Hayon, Yohanes Pande, 2000. Logika Prinsip-Prinsip
Bernalar Tepat Lurus dan Teratur. Jakarta: Penerbit
ISTN.
Hurley, Patrick J. & Lori Watson, 2018 [2012]. A Concise
Introduction to Logic. 13th Edition. Boston: Cengage
Learning.
Kane, Danielle, 2023. Disciplinary-Specific Critical
Thinking in Sociology. In Sergio A. Cabrera & Stephen
Sweet. Handbook of Teaching and Learning in
Sociology. Glethenham: Edward Edgard Publishing.
Kane, Danielle; and Kristin Otto, 2017. Critical
Sociological Thinking and Higher-level Thinking: A
Study of Sociologists' Teaching Goals and
Assignments. Teaching Sociology 1-11. DOI:
10.1177/0092055X17735156.
Kawulich, Barbara; Mark W. J. Garner; Claire Wagner,
2009. Students' Conceptions-and Misconceptions-of
Social Research. Qualitative Sociology Review Volume
V, Issue 3.
Kelle, Udo, 2014. Theorization from Data. In Uwe Flick
(Editor). The Sage Handbook of Qualitative Data
Analysis. London & Thousand Oaks: Sage
Publications.
Kennedy, Brianna L. and Robert Thornberg, 2018.
Deduction, Induction, and Abduction. Uwe Flick
(Editor). The Sage Book of Qualitative Data Collection.
London & Thousand Oaks: Sage Publications.
Marshall, Catherine and Gretchen B. Rossman, 2016.
Designing Qualitative Research. Sixth Edition.
London: Sage.
Medley-Rath, Stephanie, 2023. Designing Core Major
Courses: Methods. In Sergio A. Cabrera & Stephen
Sweet. Handbook of Teaching and Learning in
Sociology. Glethenham: Edward Edgard Publishing.
Maxwell, Joseph A., 2022. Generalization as an Issue for
Qualitative Research Design. In Uwe Flick (Editor).
The Sage Handbook of Qualitative Research Design.
London & Thousand Oaks: Sage Publications.
ICHELS 2024 - The International Conference on Humanities Education, Law, and Social Science
604
Maxwell, Joseph A. and Margaret Chmiel, 2014a. Notes
Toward a Theory of Qualitative Data Analysis. In Uwe
Flick (Editor). The Sage Handbook of Qualitative Data
Analysis. London & Thousand Oaks: Sage Publications.
Maxwell, Joseph A. and Margaret Chmiel, 2014b.
Generalization in and from Qualitative Analysis. In
Uwe Flick (Editor). The Sage Handbook of Qualitative
Data Analysis. London & Thousand Oaks: Sage
Publications.
Mekolichick, Jeanne, 2022. Undergraduate Research in
Sociology: Cultivating the Sociological Imagination.
Mieg, Harald A et.al (Editors). The Cambridge
Handbook of Undergraduate Research. Cambridge:
Cambridge University Press.
Miles, Mattew B and A. Michael Huberman, 2014.
Qualitative Data Analysis: a Methods Sourcebook.
Third Edition. Sage Publication.
Miles, Cindy L. & Cynthia Wilson, 2004. Learning
Outcomes for the Twenty First Century: Cultivating
Student Success for College and the Knowledge
Economy. New Directions for Community Colleges,
No. 126: 87-100.
Moleong, Lexy J., 2019 [1988]. Metodologi Penelitian
Kualitatif. Bandung: Remaja Rosdakarya.
Morse, Janice M., 2006. Reconceptualizing Qualitative
Evidence. Qualitative Health Research, Vol. 16 No. 3,
March 2006 415-422 DOI:
10.1177/1049732305285488.
Muminin, Iman S, 2022. Belajar Mudah Ilmu Mantiq:
Ulasan Memudahkan Atas as-Sullam al-Munawroq
Karya al-Akhdari. Jakarta: Penerbit Qaf.
Mulyana, Deddy, 2010. Metodologi Penelitian Kualitatif.
Bandung: Remaja Rosdakarya.
Neuman, W. Lawrence. 2014. Social Research:
Qualitative and Quantitative Approaches. Fifth
Edition. Boston: Pearson Education Inc.
Nind, Melanie (Editor), 2023. Handbook of Teaching and
Learning Social Research Methods.Glethenham:
Edward Edgard Publishing.
Nind, Melanie & Sarah Lewthwaite, 2019. A Conceptual-
Empirical Typology of Social Science Research
Methods Pedagogy. Research Papers in Education,
DOI: 10.1080/02671522.2019.1601756.
Nuruddin, Muhammad, 2020. Ilmu Mantik: Panduan
Mudah dan Lengkap untuk Memahami Kaidah
Berpikir. Depok: Keira Publishing.
Orange, Amy, 2023. Facilitating Learners' Reflexive
Thinking in Qualitative Research Courses. In Nind,
Melanie. Handbook of Teaching and Learning Social
Research Methods. Glethenham: Edward Edgard
Publishing.
Perdue, William D., 1986. Sociological Theory. Mayfield
Pub Co.
Rahmat, Abdi, 2020. Rencana Pembelajaran Semester
Metode Penelitian Kualitatif Tahun 2020. Jakarta:
Program Studi Pendidikan Sosiologi Universitas Negeri
Jakarta.
Reichertz, Jo, 2014. Induction, Deduction, Abduction. In
Uwe Flick (Editor). The Sage Handbook of Qualitative
Data Analysis. London & Thousand Oaks: Sage
Publications.
Ritzer, George, 1975. Sociology: A Multiple Paradigm
Science. Allyn and Bacon.
Sambas, Syukriadi, 1996 [2017]. Mantik: Kaidah Berpikir
Islami Thinking Rules. Bandung: Remaja Rosdakarya.
Schreier, Margrit, 2018. Sampling and Generalization. In
Uwe Flick (Editor). The Sage Book Qualitative Data
Collection. London & Thousand Oaks: Sage
Publications.
Suryana, Asep, 2012. Menangkap Tanda-Tanda Bermakna:
Strategi Pembelajaran Riset Kualitatif untuk Program
Sarjana. Jurnal Komunitas Prodi Sosiologi Universitas
Negeri Jakarta.
------------------, 2020. Membangun Keadilan Kota dari
Bawah: Gerakan Lokal Muhammadiyah di Post-
Suburban Depok. Depok: Disertasi Departemen
Sosiologi Universitas Negeri Jakarta.
Swedberg, Richard, 2017. Theorizing in Sociological
Research: A New Perspective, a New Departure?.
Annual Review of Sociology 43:189-206.
Https://doi.org/10.1146/ annurev- soc-060116-053604.
Swedberg, Richard, 2016. Before theory comes theorizing
or how to make social science more interesting. The
British Journal of Sociology 67 (1): 5-22. DOI:
10.1111/1468- 4446.12184.
Swedberg, Richard, 2012. Theorizing in sociology and
social science: turning to the context of discovery.
Theory and Society 41:1-40. DOI 10.1007/s11186-011-
9161-5.
Tambunan, Shuri Mariasih Gietty and Manneke Budiman,
2022. Undergraduate Research in Indonesia. Edited by
Mieg, Harald A. et.al. (Editors) The Cambridge
Handbook of Undergraduate Research. Cambridge:
Cambridge University Press 2022.
Thorn, Richard & Peter H. Sydenham, 2008. Developing a
measuring systems body of knowledge. Measurement
41: 744-754.
Thornberg, Robert, 2022. Abduction as a Guiding Principle
in Qualitative Research Design. In Uwe Flick (Editor).
The Sage Handbook of Qualitative Research Design.
London & Thousand Oaks: Sage Publications.
Thornberg, Robert and Kathy Charmaz, 2014. Grounded
Theory and Theoretical Coding. In Uwe Flick (Editor).
The Sage Handbook of Qualitative Data Analysis.
London & Thousand Oaks: Sage Publications.
Wagnera, Claire; Mark Garnerb and Barbara Kawulichc,
2011. The State of the Art of Teaching Research
Methods in the Social Sciences: Towards a Pedagogical
Culture. Studies in Higher Education Vol. 36, No. 1.
Willig, Carla, 2014. Interpretation and Analysis. In Uwe
Flick (Editor). The Sage Handbook of Qualitative Data
Analysis. London & Thousand Oaks: Sage
Publications.
Wuisman, J.J.M, Jan, 2004. Realisme Kritis: Pemahaman
Baru tentang Penelitian Ilmu Sosial. Dalam Jurnal
Masyarakat dan Budaya Vol. VI No. 2. Jakarta: Pusat
Penelitian Kemasyarakatan dan Kebudyaan Lembaga
Ilmu Pengetahuan Indonesia
Reconceptualizing Empirical Data:Developing Higher Order Thinking Skills in Undergraduate Qualitative Methods Learning
605
Zlatkin-Troitschanskaia, Olga et.al. (Editors). 2018.
Assessment of Learning Outcomes in Higher
Education: Cross-National Comparisons and
Perspectives. Switzerland: Springer International
Publishing.
ICHELS 2024 - The International Conference on Humanities Education, Law, and Social Science
606