Loading presentation...

Present Remotely

Send the link below via email or IM

Copy

Present to your audience

Start remote presentation

  • Invited audience members will follow you as you navigate and present
  • People invited to a presentation do not need a Prezi account
  • This link expires 10 minutes after you close the presentation
  • A maximum of 30 users can follow your presentation
  • Learn more about this feature in our knowledge base article

Do you really want to delete this prezi?

Neither you, nor the coeditors you shared it with will be able to recover it again.

DeleteCancel

2017 12 New Qualitative and Quantitative Approaches

No description
by

Chin-Chung Tsai

on 20 December 2017

Comments (0)

Please log in to add your comment.

Report abuse

Transcript of 2017 12 New Qualitative and Quantitative Approaches

Outline

Purposes of conducting a review paper


Examples of qualitative review studies


Small-sized content analysis (6 papers)


Examples of quantitative review studies


Large-scaled content analysis (3 papers)


Co-citation network analysis (1 paper)
Examples of qualitative
review studies

Small-sized content analysis
Q&A
1. The minimal number of
papers collected for a
review paper.
2. The effective approach to
writing a review paper.
3. The time period selected for
the review.
4. The literature review for
literature review paper.
Examples of
quantitative review studies


Large-scaled content analysis
1.
Hsu, Y.-C., Ho, H. N. J., Tsai, C.-C., Hwang, G.-J., Chu, H.-C.,
Wang, C.-Y., & Chen, N.-S. (2012). Research Trends in
Technology-based Learning from 2000 to 2009: A Content
Analysis of Publications in Selected Journals. Educational
Technology & Society, 15 (2), 354–370.
2.
Wu, Y.-T., Hou, H. T., Hwang, F.-K., Lee, M.-H., Lai, C.-H.,
Chiou, G.-L., Lee, S. W.-Y., Hsu, Y. C., Liang, J.-C., & Chen,
N.-S., & Tsai, C.-C. (2013). A review of intervention studies on
technology-assisted instruction from 2005-2010. Educational
Technology & Society, 16(3), 191-203.
3.
Lin, T. C., Lin, T. J., Tsai, C. C. (2014). Research trends in
science education from 2008 to 2012: a systematic content
analysis of publications in selected journals. International
Journal of Science Education, 36(8), 1346-1372.


Co-citation network analysis
4.
Tang, K. Y., Tsai, C. C., Lin, T. C. (2014). Contemporary
intellectual structure of CSCL research (2006–2013): a co-
citation network analysis with an education focus. International
Journal of Computer-Supported Collaborative Learning, 9(3),
335-363.

Qualitative and Quantitative Approaches
Writing a Literature Review Paper:
Chin-Chung Tsai, Chair Professor
Computers & Education
, Co-Editor
International Journal of Science Education,
Editor

Program of Learning Sciences,
National Taiwan Normal University

Purposes of conducting a review paper

‘Writing for publication’ (Tsai and Wen, 2005), and
literature review papers often get high citations

‘Information about the current status and trends of
research in the fields’ (Lee, Wu, and Tsai, 2009)

‘Share knowledge of researchers’ - Researchers can
popularize their research findings in the academic
community’ (Lin, Lin, and Tsai, 2014)

To frame a theoretical foundation of existing
literature for future research (Li and Tsai, 2013; Lee
and Tsai, 2013; Hsin, Li, and Tsai, 2014)

Graphically present the intellectual structure of
research discipline (Tang, Tsai, and Lin, 2014)

1.
Li, M. C., Tsai, C. C. (2013). Game-based learning in science
education: a review of relevant research. Journal of Science Education
and Technology, 22(6), 877-898.
2.
Lee, S. W.-Y., & Tsai, C.-C. (2013). Technology-supported learning in
secondary and undergraduate biological education:Observations from
literature review. Journal of Science Education and Technology,
22(2),226-233
3.
Lai, M.-L., Tsai, M.-J., Yang, F.-Y., Hsu, C.-Y., Liu, T.-C., Lee, S. W.-Y.,
Lee, M.-H., Chiou, G.-L., Liang, J.-C., & Tsai, C.-C. (2013). A review of using
eye-tracking technology in exploring learning from 2000 to 2012. Educational
Research Review, 10, 90-115.
4.
Chang, H-Y., Wang, C-Y., Lee, M-H., Wu, H-K., Liang, J-C., Lee, Silvia W.-Y.,
Chiou, G-L., Lo, H-C., Lin, J-W., Hsu, C-Y., Wu, Y-T., Chen, S., Hwang, F-K.,
& Tsai, C-C. (2015). A review of features of technology-supported learning
environments based on participants’ perceptions, Computers in Human
Behavior, 53, 223–237.
5.
Cheng, K.-H., & Tsai, C.-C. (2013). Affordances of augmented reality in
science learning: Suggestions for future research. Journal of Science
Education and Technology, 22(4), 449-462.
6.
Deng, F., Chen, D. T., Tsai, C. C., & Chai, C. S. (2011). Students' views
of the nature of science: A critical review of research. Science
Education, 95(6), 961-999.
1.
Game-based learning in science education:
A review of relevant research (2013),
Journal of Science Education and Technology

Paper Selection and Analysis


31 empirical papers were identified for review.

The coding scheme for game-based learning in
science learning research using four theoretical
viewpoints including (1) cognitivism, (2)constructivism,
(3) the socio-cultural perspective,and (4) enactivism.

Coding scheme for game-based learning in science learning research
Source: Li and Tsai (2013)

A theoretical framework of the game-based learning in science learning
Source: Li and Tsai (2013)
Conclusions

The results indicate that cognitivism and
constructivism were the major theoretical
foundations employed by the game-based
science learning (GBSL) researchers


The socio-cultural perspective and enactivism
are two emerging theoretical paradigms
that have started to draw attention from GBSL
researchers in recent years.
2.
Technology-supported learning in secondary and
undergraduate biological education: observations
from literature review (2013),
Journal of Science
Education and Technology

Paper selection


Using educational technology in biology learning from
2001 to 2010. A total of 36 empirical articles were
included for review.

Research method:


We used an inductive method to develop coding
categories and identify patterns across differentstudies.
The two reviewers developed consensus when
disagreement emerged. At the end, we counted the
frequency of occurrence of the categories.
Results

Based on a content analysis, four observations
were concluded (Lee and Tsai, 2013).

The 1st Observation: Among different types of
technologies, the majority of studies utilized
simulation/visualization, multimedia/online
materials, or integrated learning systems.
pedagogies that guided the instructional design
were explicitly stated in only a few studies.
The 2 Observation
nd

Genetics and molecular biology were the
most popular biological topics taught with
the application of educational
technologies. however, only a few studies
included interdisciplinary content.
The 3 Observation
rd

Most studies assessed students’ acquisition
of knowledge, fewer studies examined
change in affective outcome, and a few
studies assess students’ skills. also a small
number of studies observed students’
learning processes.
The 4 Observation
th

Beyond the comparison for traditional
teaching versus technology-assisted learning,
some studies examined the impact of
different technology affordance on biology
learning.
Conclusions

This review study concluded some trends of using
technology for biological education (2001-2010).

We expect these two trends—blended learning and
computer-supported assessment will continue to
grow for undergraduate education.

The application of educational technologies for teaching
mathematical biology (Norris et al. 2009) and
quantitative skills in biology (Thompson et al. 2010).

Technology-supported learning for problem solving,
especially in an interdisciplinary context.

how educational technologies can facilitate learning of
biological concepts.
3.
A review of using eye-tracking technology in
exploring learning (2013),
Educational
Research Review

Paper selection

A total of 81 papers were selected from the SSCI database (2000-2012).


The content analysis consisted of three stages (coding procedure):

(1) the content of a selected paper was preliminarily coded based on its
learning topics to specify different aspects of cognitive development.

(2) all papers of different learning topics were then coded for the
research questions or tasks, eye movement measures and
indications drawn from these eye movement measures.

(3) several thematic linkages were generated through cross-
examination of the research questions/tasks and the eye movement
indications identified in each paper. The thematic linkages were
defined as ‘‘learning themes.’’
Coding scheme used to analyze the learning topics

Selected papers were content-analyzed based on
its learning topics to specify different aspects of
cognitive development.
Source: Lai et al. (2013)
Bridging framework between eye movements and learning
Source: Lai et al. (2013)
Conclusions

Content analysis showed that eye movements and
learning were studied under the following seven themes:

patterns of information processing

effects of instructional design

reexamination of existing theories

individual differences

effects of learning strategies

patterns of decision making

conceptual development

This study concludes that the eye-tracking method
provides a promising channel for educational researchers
to connect learning outcomes to cognitive processes.
2.
A review of intervention studies on
technology-assisted instruction from 2005-2010 (2013),
Educational Technology & Society

Paper selection


a total of 322 articles out of 4,093 were selected
for the analyses in this study.

Coding scheme. The coding scheme used in this
study consists of six major categories:


Sample groups


Subject domain


Research focus


Technology adoption


Interpersonal interaction type


Participant interaction
Cross analysis results:
Source: Wu et al. (2013)
Source: Wu et al. (2013)
Cross analysis results:
technology adoption vs. subject domain
Source: Wu et al. (2013)
Cross analysis results:
Interpersonal interaction type vs. participant interaction
Source: Wu et al. (2013)
Conclusions

In this study, a remarkable increase in the number of
empirical studies on technology-assisted instruction from
2005 to 2010 was found.

Very few studies have simultaneously addressed
achievement, learning process, and affective outcomes.

This suggests that further research on technology-
assisted instruction may be conducted with various samples,
different subject domains, or multiple research foci.

Digital literacy outcomes and metacognitive knowledge have
received an increasing amount of attention in recent years.


Future research can also include these outcomes when
analyzing the research foci among the reviewed studies.
3.
Research trends in science education from 2008 to 2012: a systematic content analysis of publications in selected journals (2014),
International Journal of Science Education

Paper selection

Identical to the previous series of investigations
examining the research trends in science education (Lee
et al., 2009; Tsai & Wen, 2005), the present study first
collected all the papers published in IJSE, JRST, and SE
from 2008 to 2012 as the preliminary samples.

‘editorial’, ‘commentary’, ‘responses’, and ‘book review’
papers were then manually excluded.

This study analyzed the final sample of 990 research
papers.
Coding and calculation



score=

n = the total number of authors in this paper,
i = the order of the specific author.

Research Type:

(1) empirical research article, (2) position paper, (3) theoretica
paper, (4) review paper, (5) other.

Research Topic:

Tsai and Wen’s (2005) categorization of 9 topics.

Authors’ Productivity:

every author’s contribution to the target papers.

Highly Cited Papers

The top 3% of papers based on citation counts were chosen as
the highly cited papers (Lee et al., 2009).

Authors’ nationality (Howard et al., 1987):
Comparisons of country ranks of publications in 1998–2002, 2003–2007, and 2008–2012 for the three journals (IJSE, JRST, and SE)
1998–2002
2003–2007
2008–2012
Comparisons of research types
Source: Lin, Lin, and Tsai (2014)
Comparisons of research topics
Comparisons of research topics (2008-2012)
Comparisons of author productivity of publications
The top 10 highly cited articles (1998–2012)
Conclusions

Researchers will gain insights into the current status of
science education research which can further suggest some
possible directions for following investigations.

This may be especially beneficial for new researchers who
have begun conducting relevant research and writing
academic publications most recently.

For science teachers, being aware of the highlighted issues
in science education will possibly encourage reflections on
and improvements in their own teaching practices.

It is important that science educators explore more
characteristics of literature and apply diverse review
techniques such as social network analysis (Scott, 2012) to
more precisely recognize the possible changes in research
trends in the future.
4.
Contemporary intellectual structure of CSCL research (2006–2013): a co-citation network analysis with an education focus (2014),
International Journal of Computer-Supported Collaborative Learning

Paper selection

a multi-keywords searching strategy is used to query
the initial data in the Web of Science.

A total of 1,438 papers were obtained, among which
692 were cited at least twice to satisfy the minimum
requirement of co-citation analysis were retained.

After removing replicated papers and incomplete
records, 403 documents were obtained and nominated
as the initial dataset for the following investigation.
The process of search
Source: Tang, Tsai, and Lin (2014)
Why using co-citation network analysis for the literature review in CSCL

Previous review works have provided insightful overviews for
field researchers based on the experienced experts’ insights.

While qualitative review research based on experts’ opinions can
provide valuable insights for understanding the development of
CSCL research, a review from a quantitative perspective based
on longitudinal data analyses is also necessary.

The existing fruitful literature provides appropriate material for the
analysis of the research trajectory in the CSCL community.

Through longitudinal data retrieval, a quantitative review can
provide a large-scale platform for further scholarly discussion.

Therefore, it is worthwhile in a field of growing CSCL literature to
use different but complementary methods to provide insights into
the ways of scholarly communication.
Three combinations of method for analyzing citation-based data (1/3)

Documents in specialized areas tended to cite some
researchers’ concepts or be co-cited by others within
the field (Small 1973).

Document co-citation analysis, one of the best-known
structuring methods of bibliometrics (Small 1973; Small
and Griffith 1974), is useful to identify authors or
documents belonging to the same discipline (or field) by
analyzing the references.

Accordingly, the current paper employed document co-
citation with additional analyses of factor analysis to
assess the contributions of documents and delineate
the distinct subfields within the realm of CSCL.
Three combinations of method for analyzing citation-based data (2/3)

Exploratory factor analysis (EFA) is a multivariate
statistical method used to reduce the number of
dimensions.

Accompanying the bibliometric purposes, EFA played
an intermediate role of analysis to extract latent common
factors and derive the subfields from the co-citation
matrix in this study(McCain 1990; White & Griffith 1981).

According to Small and Griffith (1974), each subfield
corresponding to the extracted factors represented an
intellectual theme defined by authors who were loaded
highly on that subfield/factor.
Three combinations of method for analyzing citation-based data (3/3)

Social network analysis was also adopted to profile
the centrality features of the co-citation network of
the selected documents (Freeman 1979).

This method permits the exploration of existing
linkages between the most central and prominent
works within the focal discipline (Wasserman and
Faust 1994; Scott 1991).

The advantage of a social network is that it can
propose a complementary viewpoint from the citation
side and provide a visualizing map of interdisciplinary
scholarly communications (White 2003).
A raw co-citation matrix of top ten co-cited CSCL papers
Source: Tang, Tsai, and Lin (2014)
Results of the exploratory factor analysis (EFA)

Six factors were extracted with 83 % of the
explained variance.

Most CSCL articles were loaded on one specific
factor with high loadings, and each factor
revealed the underlying subject matter (loading
greater than ±0.7) (McCain 1990).

Each factor was named based on a general
assessment of the research areas represented
by documents with leading factor loadings as
well as the terminology used in the CSCL
literature.
Example of EFA (first two factors)
Summary of exploratory factor analysis
Source: Tang, Tsai, and Lin (2014)
Co-citation networks of whole sample of 403 CSCL research from 2006 to 2013
Source: Tang, Tsai, and Lin (2014)
A close look at CSCL research network
Conclusions

This is the very first attempt to integrate the
bibliographical method, statistical analysis, and
visualization techniques to investigate the
intellectual structure of CSCL empirical studies.

As a result, six intellectual subfields are mapped,
and major core documents and publications were
identified.

In addition, several boundary spanning
documents and research trends within the CSCL
field were presented and discussed.
Three other published papers using co-citation network analysis

The intellectual structure of research on
educational technology in science education
(ETiSE): A co-citation network analysis of
publications in selected journals (2008-2013)

The intellectual structure of
metacognitive
scaffolding in science education
(1995-2014):
co-citation network analysis

A co-citation network of
young children’s
learning with technology.
exploration and extension


Introduction

This is a synthesis study of instruments and factors
measuring participants’ perceptions of technology-
supported learning environments (TSLE).

The purpose of the review is to identify key elements of
technology-supported learning environments (TSLE)
through participants’ perceptions.
Methods

We used the Web of Science to search for research
articles.

The keywords include three sets:






The time span was set from 1998 to 2014 to follow up
on the review by Fraser (1998a) and to include the
current status.

Methods

A total of 210 papers returned.

We further examined whether these studies
1.relate to technology-assisted learning,
2.focus on the development of a
questionnaire (or questionnaires) and
3.address participants’ perceptions of the
learning environment.

As a result, 22 representative studies were
selected, coded and analyzed in this study.
Results

Through categorizing the factors/scales of the
perception instruments reported in the studies, We
identified six important dimensions of TSLEs including
technical, content, cognitive, metacognitive, social and
affective.

Conceptualization of a Framework for Technology-Supported Learning Environments
Conceptualization of a Framework for Technology-Supported Learning Environments
Conceptualization of a Framework for Technology-Supported Learning Environments
Concluding remarks

The framework can be used for future development
of instruments of TSLE.

Usability in the technical dimension, relevance in the
content dimension, inquiry learning in the cognitive
dimension, student autonomy in the metacognitive
dimension, and teacher support in the social
dimension, are the salient features most often
investigated in TSLEs.

No specific pattern was observed for the affective
dimension.

Future research can explore the less addressed
dimensions, especially the metacognitive dimension.
Appendix A. Overview of the Instruments and Their Validities and Reliabilities
Appendix A. Overview of the Instruments and Their Validities and Reliabilities
4.
A review of features of technology-supported
learning environments based on participants’
perceptions (2015),
Computers in Human Behavior
5.
Affordances of augmented reality in science
learning: Suggestions for future research

This review paper firstly has identified two major
approaches of utilizing AR technology in science
education, which are named as image-based
AR and location based AR. These approaches
may result in different affordances for science
learning. It is then found that students’ spatial
ability, practical skills, and conceptual
understanding are often afforded by image-
based AR and location-based AR usually
supports inquiry-based scientific activities.

The purposes of this paper
1.
To identify the current features of AR
technology in science education.
2.
To understand the affordances of AR in
science learning.
3.
To examine the focal point of the current
research on AR-related science learning.
4.
To make suggestions for future science
research regarding AR-related learning.
1. Features of Augmented Reality
(1)
Image-Based AR

Basically, marker-based AR
requires specific labels to
register the position of 3D
objects on the real-world
image.

As presented in Fig. 2, an AR
book with basic equipment
such as a webcam and
marker labels is one of the
typical marker-based
applications and has been
employed in several studies.
(2)
location-based AR

In contrast to image-
based AR, markerless
AR uses position data
launched from mobile
devices, such as a
wireless network or
global positioning
system (GPS), to
identify a location,
and then superimposes computer-generated
information (as illustrated in Fig. 4). Several
studies have demonstrated location-aware AR
educational games with mobile devices.

A Comparison of Image-Based and Location-Based AR

To clearly identify the
similarities and differences
between image-based and
location-based AR, Fig. 5
illustrates a comparison.
While the recognition of
artificial labels or natural
graphics is the main
feature of image-based
AR, GPS or a wireless
network is used as the
recognition technique to register users’ positions and to
offer them real time information in a location-based AR
environment.
2.

Affordances of AR in Science Learning

12 articles regarding AR-related work were chosen for
analysis. As shown in Table 1, the technical features,
focus topics, participants, and affordances in science
learning of these studies are summarized.
3. To examine the focal point of the current research on AR-related science learning

To fully describe what has been investigated in
AR-related science learning from a pedagogical
perspective, the VR-based learning model
(Salzman et al. 1995) was used as a basis for
examining the affordances of AR in science
learning.

The selected articles are discussed according to
the dimensions in the model (i.e., technical
features, science concepts, learner
characteristics, interaction experience, learning
experience, learning process, and learning
outcomes).
Technical Features and Science Concepts
1.
Image-Based AR for Spatial Ability, Practical Skills,
and Conceptual Understanding

The image-based AR technology utilized in the selected studies allows users
to manipulate a plate with a marker to comprehend the 3D structure of
augmented virtual objects. These studies have extended this characteristic
to enhance learners’ scientific spatial ability (Kerawalla et al. 2006),
conceptual understanding (Koong Lin et al. 2011), and conceptual change
(Shelton and Stevens 2004). Also, with the auxiliary information about
physical elements superimposed on a display (e.g., a computer screen or
seeing through an HMD) provided by image-based AR technology, learners’
practical skills (Andujar et al. 2011) regarding science learning are most
likely enriched based on their experiences in physical environments such as
laboratories.

2.
Location-Based AR and Scientific Inquiry Learning

On the other hand, the selected studies indicate a trend that the applications of
location-based AR are likely to support collaborative inquiry-based activities in
science learning (O’Shea et al. 2011). Location-based AR technology is
characterized as position-free and developed within the context of physical
environments; therefore, it provides more opportunities to design activities for
learners to make inquiries into scientific topics.
Learning Process and Learning Outcomes
Learning Experience and Interaction Experience
Learner Characteristics

Most of the studies regarding the utilization of image-based AR did not clearly
explore the students’ learning process or examine their learning outcomes.
Compared with image-based AR, the studies regarding the utilization of
location-based AR (i.e., Squire and Klopfer 2007; O’Shea et al. 2011;
Rosenbaum et al. 2007; Squire and Jan 2007; Dunleavy et al. 2009) did
thoroughly explore the participants’ inquiry-based science learning process
with qualitative methods such as interviews, observations, or videotaping
analysis. These studies emphasized the students’ interactive discourse to
describe the process of forming initial problems, constructing group goals,
exchanging or negotiating information with group members, planning
solutions, and developing shared understandings. Through the discourse,
these studies also qualitatively indicated a result for the improvement of
students’ scientific practice and thinking ability.

In general, students in the image-based AR setting showed positive interaction
experience when learning. In the location-based AR setting, students mostly
expressed positive learning experiences and were highly motivated.

Among the selected articles, there were only three studies examining the learner
characteristics when students were involved in AR-related science learning
An overview of AR research issues in science learning

To clearly conclude this review of what has been done in science learning
with AR supports, Fig. 6 has been generated to address several issues and
research methods according to the selected studies. As shown in Fig. 6, the
research of image-based AR in science learning mainly emphasizes the
evaluation of users’ interactive experience, such as their perceived usability
of the AR applications
4. Suggestions for Future Research
To summarize, Fig. 7 is illustrated for addressing that the four theories could be substantially germane to the unique affordances provided by AR technology. Also, AR research in science education is suggested to be guided by these theories in the future.
6.
Students' views of the nature of science: A critical review of research

This review examines 105 empirical studies that
investigate students’ views of the nature of science
(VNOS), effects of curricular interventions on changing
students’ VNOS, and relations between VNOS and
demographics, majors, and learning of science.

The reviewed studies can be categorized into three
theoretical frameworks: the unidimension, the
multidimension, and the argumentative resource
frameworks.

Each framework is reviewed first with regard to its
theoretical foundation, methods of data collection and
analysis, and the respective findings. This is followed by
a critical discussion on the methodological issues and
the strengths and limitations of the framework.
Method
1.
This review examines empirical research on students’
VNOS ranging from primary school to postgraduate
within the domains of science education.
2.
Two techniques were used to search literature: the
online database approach and the ancestry approach.
● 
Four online databases were initially searched with the following
   keywords: “nature of science,” “NOS and student *,”
   “epistemological belief * and science,” “epistemological view * and
   scientific,” “epistemology of science and student *,” “scientific
   epistemology,” and “nature of scientific knowledge and student *.”
   The databases are Academic Search Premier, ERIC, Education
   Research Complete, and PsycINFO. The search resulted in 82
   articles that fit the purpose for this review.
● 
By tracing references of the 82 studies, the ancestry approach
   helped to identify another 23 articles. A total of 105 articles were
   selected for the final review.
Theoretical frameworks

The 105 reviewed studies can be categorized into three
   theoretical frameworks.
1.
The unidimension (UD) framework perceives VNOS as a continuum
ranging from empiricist to mixed, and to constructivist perspectives.
2.
The multidimension (MD) framework argues that VNOS aremade up of
multiple dimensions that aremore or less independent. In general,
these two-dimensionoriented frameworks do not seem to focus on the
role of context. They also treat VNOS as certain “entities” held in the
minds of the students or cognitive structures possessed by students.
3.
Instead of treating VNOS as properties of individuals, the
argumentative resource (AR) framework suggests that VNOS should
be seen as discursive achievements (Roth & Lucas, 1997) that are
illustrated through argumentative resources drawn in practice. The AR
framework also focuses more on whether students can critically reason
scientific issues in an “appropriate” way (e.g., Ford, 2008a, 2008b)
rather than whether they can “correctly” report their VNOS in manners
that are consistent with those NOS aspects advocated by science
educators (e.g., McComas & Olson, 1998).
FUTURE DIRECTIONS

Theoretical Implications
Suggestion 1:
A Reexamination of The MD Framework.
Future studies can examine the extent to which NOS dimensions are independent. As the MD framework suggests, VNOS is a system of more-or-less independent dimensions that may not develop in a coherent way. However, it remains unclear as to the degree of the independence among these dimensions.
Suggestion 2:
More Attention to the AR Framework.
Future research could pay more attentions to the AR framework for at least two reasons. First, as discussed previously, the AR framework addresses the limitations of both the UD and MD frameworks. Second, this framework seems to help explain several findings reported by studies guided by the other two frameworks. A suggestion for concerning the AR framework, however, does not indicate the abandonment of the dimensional frameworks (UD and MD) in future research.
Suggestion 3:
A Refinement of the “Sophistication” Criteria.
Future studies could focus on studying how to determine the sophistication of VNOS through students’ argumentation of scientific claims rather than their professed statements about NOS.

Methodological Implications
Suggestion 4:
An Emphasis on the Qualitative Methods.
More than half of the reviewed studies employed open form instruments and content analysis. Future research could place more emphasis on qualitative methods for both data collection and analysis.

Pedagogical Implications
Suggestion 5:
An Attention to the Epistemic and Social
Aspects of Inquiry.
Future research could pay more attention to the epistemic-social aspects of inquiry when preparing curricular interventions for changing students’ VNOS.
Directions of Qualitative approach

Conduct content analysis




Propose a Typology

Re-define existing
concept/construct/trend/idea or re-
categorize existing research literatures
Theoretical underpinnings
Research methods/techniques
Research findings
Content analysis for qualitative approach

Manual (labor-intensive)

System/Software/text mining
Directions of Quantitative approach

Get a large picture for research
topics / sample / method…

Explore the interplay between these constructs

Rank research trend / country / author / highly
cited papers

The networking among research
work / topic / author

Meta-analysis
1.
Research Trends in Technology-based Learning from 2000 to 2009: A content Analysis of Publications in Selected Journals

This paper provides a content analysis of studies in
technology-based learning (TBL) that were
published in five selected journals (i.e. British
Journal of Educational Technology, Computers &
Education, Educational Technology Research &
Development, Educational Technology & Society,
the Journal of Computer Assisted
Learning) from 2000 to 2009.

A total of 2,976 articles were cross-analyzed
by three categories including research topic,
research sample group, and learning domain.
The Chi-square analysis results showed that
there were significant associations among
these three categories.
Coding framework
A total of 2,976 articles were coded by:
● Research topics:
Development of Learning Systems, Platforms and Architectures, 2. Evaluation of Learning Systems, Platforms and Architectures, 3. Pedagogical Design and Theories, 4. Adaptive and Personalized Technology-Enhanced Learning: Knowledge and Competencies Management, 5. Artificial Intelligence in Education, 6. Computer Supported Collaborative Learning, 7. Mobile and Ubiquitous Learning, 8. Digital Game and Intelligent Toy Enhanced Learning, 9. E-Assessment and New Assessment Theories and Methodologies, 10. Special Needs Education, 11. Motivation, Perceptions and Attitudes, 12. Learning Behaviors, Usage Patterns and Discourse Analysis, 13. Policies, Social Culture Impacts and Trends for Technology-Enhanced Learning
● Research sample groups:
Elementary school, 2. Junior and Senior high school, 3. Higher education, 4. Teachers, 5. Adults, 6. Others, and 7. Non-specified.
● Research learning domains:
Science (e.g. Physics, Chemistry, and Biology, Medical and Sport Science), 2. Mathematics, 3. Arts & Language, 4. Social Studies, 5. Engineering (including Computers), 6. Others, and 7. Non-specified.
Research questions (RQs)
1.
What research topics related to technology-based learning were
published in these selected journals from 2000 to 2009? And what were
the topic variations between the first five years (2000-2004) and the
second five years (2005-2009)?
2.
What research sample groups related to technology-based learning were
selected in these published articles from 2000 to 2009? And how did the
sample group selections shift between the first five years (2000-2004)
and the second five years (2005-2009)?
3
. What research learning domains related to technology-based learning
were adopted in these published articles from 2000 to 2009? And how
did the learning domain shift between the first five years (2000-2004) and
the second five years (2005-2009)?
4.
Is there any significant association between the research topic and the
selection of the research sample group for these publications from 2000
to 2009?
5.
Is there any significant association between the research topic and the
adoption of the learning domain for these publications from 2000 to 2009?

RQ1
: What research topics related to technology-based learning were published in these selected journals from 2000 to 2009? And what were the topic variations between the first five years (2000-2004) and the second five years (2005-2009)?
From 2000 to 2004, the most published research topic was “Pedagogical Design and Theories” (249.4). The least published research topic was “Digital Game and Intelligent Toy Enhanced Learning” (8.8).
On the other hand, from 2005 to 2009, the most published research topic was “Pedagogical Design and Theories” (501.7). The least published research topic sub-category was “Special Needs Education” (19.4).
The results of the Pearson’s Chi-Square analysis revealed that the published research topics were significantly different between the initial five years (2000-2004) and the latest five years (2005-2009) (p<0.05). The major difference was that the “Policies, social culture impacts and trends for technology-enhanced learning” research sub-category showed a declining trend (from 14.13% to 6.71%).
RQ2
: What research sample groups related to technology-based learning were selected in these published articles from 2000 to 2009? And how did the sample group selections shift between the first five years (2000-2004) and the second five years?
From 2000 to 2004, research samples in “Higher Education” were utilized most (399.8). The least employed research sample was “Others” (13.0).
From 2005 to 2009, research samples in “Higher Education” were still used for most of the TBL research papers (830.1). However, the number of articles in the “Non-specified” group reduced from 301.1 to 269 between the two periods.
The results of the Pearson’s Chi-Square analysis also showed that the research sample groups were significantly different between the initial five years (2000-2004) and the more recent five years (2005-2009) (p<0.05). The major difference was that the sample group “Non-specified” declined from 27.65% to 14.93% and the recruited samples in “Higher Education” increased from 36.71% to 46.07% between the two periods.
RQ3:
What research learning domains related to technology-based learning were adopted in these published articles from 2000 to 2009? And how did the learning domain shift between the first five years (2000-2004) and the second five years?
From 2000 to 2004, the “Nonspecified” learning domain was found in most of the TBL publications (n=501). From 2005 to 2009, the number one ranked learning domain was still “Non-specified” (n = 644.5).
The results of the Pearson’s Chi-Square analysis also reported that the adoption of learning domain was significantly different between the initial five years (2000-2004) and the later five years (2005-2009) (p<0.05). The major difference was that the research trend in “Engineering” increased from 12.49% to 21.0% while the “Nonspecified” learning domain decreased from 46.01% to 35.77%, even though the number of published articles in the “Non-specified” learning domain increased between these two periods. Studies in “Math” and “Others” also had more growth between the two periods.
RQ4:
Is there any significant association between the research topic and the selection of the research sample group for these publications from 2000 to 2009?
RQ5:
Is there any significant association between the research topic and the adoption of the learning domain for these publications from 2000 to 2009?
Tsai, C.-C. (2000). A Typology of the Use of Educational Media, with Implications for Internet-Based Instruction.
Educational Media International
, 37, 157-160.
Full transcript