# data[].attributes.headline
นายธนสร ดอนน้อย 6202

# data[].attributes.body
นายธนสร ดอนน้อย 620210155

# data[].attributes.attachment_link.title
แผนหน้าเดียว-เซลล์กัลวานิก(model-based)-นายธนสร ดอนน้อย-620210155

# data[].attributes.headline
ครีม 159 การปรับเปลี่ยนโครงสร้างพอลิเมอร์ Modified starch และ Gelling agent

# data[].attributes.subject
ครีม 159 การปรับเปลี่ยนโครงสร้างพอลิเมอร์ Modified starch และ Gelling agent

# data[].attributes.headline
การใช้โมเดล 3 มิติแก้ไขปัญหาโครงสร้างโมเลกุลของสาร

# data[].attributes.subject
การใช้โมเดล 3 มิติแก้ไขปัญหาโครงสร้างโมเลกุลของสาร

# data[].attributes.body
https://www.degruyter.com/document/doi/10.1515/cti-2019-0005/html

# data[].attributes.attachment_link.readable_text
Introduction

Additive manufacturing, commonly known as 3D printing, refers to technologies that build 3D objects by adding material layer by layer. Added material can be, for example, plastic or metal; the former is the most used in chemistry education ( Bharti & Singh, 2017). Additive manufacturing has many advantages compared to traditional processes. Firstly, in many cases it is easier to produce complex artefacts additively than subtractive (e.g. CNC machining) ( Jamie, 2018; Lolur & Dawes, 2014). Secondly - and most importantly - the waste of raw material is minimal, supporting environmentally friendly and sustainable chemistry thinking ( Andraos & Dicks, 2012).

Additive manufacturing is a rapidly growing field. Although currently it is only a marginal part of the entire manufacturing industry, it is nevertheless considered a common production method alongside traditional methods ( Long, 2018). It is already an essential technique for digital manufacturing and home fabrication, and the general consensus is that 3D printing will be one of the next major technological revolutions ( Rayna & Striukova, 2016).

According to Hart (2017a), fast growth has created a skill gap in additive manufacturing. The rising industry is struggling to find people skilled in 3D printing and is looking for support from the education sector. The additive manufacturing industry has a great need for experts; the education sector has the possibility and responsibility to respond to this demand ( Hart, 2017a, Hart). This need has been recognized in schools, and enthusiastic teachers worldwide are developing pedagogical models on the integration of 3D printing in school curricula. At the same time, the price of 3D printers has decreased, enabling more schools to purchase the technology ( Litts, 2015). Expectations are high - teachers using 3D printing have reported that it supports the development of multiple skills relevant for the 21 st century, such as 3D modelling, creativity, and important learning skills (e.g. critical thinking, problem-solving and self-directed learning) ( Trust & Maloy, 2017). Enthusiasm about 3D printing as an educational innovation is massive, however Nemorin and Selwyn (2017) argued that integrating 3D printing in a learning context is a challenging design task for the learning environment. Hence, it is important to understand how this new technology is being used in schools, and if it represents a new innovative form of education. According to their research, there were many cases where such new technology was used to support the traditional behaviourist way of teaching and learning. Nemorin and Selwyn (2017) research findings, however, conflict with the hopes that are set for educational 3D printing ( Trust & Maloy, 2017).

Nemorin and Selwyn (2017) suggest that the pedagogical use of 3D printing might change over time, after more teachers and students become familiar with the makerspace culture. It could change the working culture around 3D printing in formal education, and 3D printing could also serve as one model for informal out-of-school learning. However, the cultural change will take time, yet the need for skilled additive manufacturers is immediate, making this topic of outmost importance in current chemistry education ( Nemorin & Selwyn, 2017).

It has been proposed that "3D printing offers nearly unlimited potential for chemical educators" ( Davis, Jones, Thiel, & Pauls, 2018). Although several articles have been published on this topic, the current state of research and pedagogical development remains unclear. The goal of the present article is to evaluate this potential via a comprehensive review of published literature on 3D printing. We approach this goal by analysing the type of publications that have been published, the reported motivation for 3D printing, and the type of learning environment design strategies that have been used. The analysis of strategies is carried out using a Technological Pedagogical Content Knowledge (TPACK) framework, which is widely used to understand the possibilities and challenges related to the pedagogical use of technology in general ( Koehler, Mishra, & Cain, 2013; Mishra & Koehler, 2006). This review summarizes the current state of 3D printing in chemistry education, which in turn should enable the development of chemistry teacher education and research that comprehensively accounts for the earlier research done in this field.

Technological pedagogical content knowledge

TPACK is a widely adopted knowledge framework that illustrates the different types of knowledge that teachers need to master for the successful use of technology in their teaching ( Koehler & Mishra 2005; 2009; Mishra & Koehler, 2006). Since its publication in 2005, there are over 900 published TPACK-related research articles ( TPACK.org, 2018). It was originally developed to respond to the criticism concerning the lack of theoretical grounding for educational technology ( Koehler & Mishra, 2005). From historical perspective, TPACK is an iteration of Shulman's Pedagogical Content Knowledge (PCK) model ( Shulman 1986; 1987), which emphasized the important interaction between pedagogical knowledge and content knowledge. PCK model was developed before the age of modern educational technology, which inspired Mishra and Koehler to redesign Shulman's ideas with the aim of explaining how teachers' understanding of how technology and PCK can interact, resulting in the successful integration of education and technology ( Koehler & Mishra, 2005; Mishra & Koehler, 2006).

The TPACK framework consists of several knowledge domains ( Figure 1). The three main components of teachers' knowledge are pedagogical knowledge (PK), content knowledge (CK), and technological knowledge (TK) ( Koehler & Mishra, 2005; Mishra & Koehler, 2006).

-

TK covers the knowledge about how to use technology (e.g. devices, software, communication tools) to support work and everyday life. TK must be constantly developed because of the rapid changes in information and communication technology (ICT) ( Koehler & Mishra, 2009; Koehler et al., 2013).

The interaction of these components forms three complex knowledge categories: pedagogical content knowledge (PCK), technological content knowledge (TCK), and technological pedagogical knowledge (TPK) ( Koehler & Mishra, 2005; Mishra & Koehler, 2006).

-

TPK is the understanding of the possibilities that technology can offer for learning. TPK does not have a subject-specific (CK) perspective ( Koehler & Mishra, 2009; Koehler et al., 2013).

TPACK is a knowledge domain that emerges from the interaction of content, pedagogy, and technology knowledge in the chosen context. It is a more versatile understanding of possibilities and challenges of ICT in teaching and learning than any other knowledge domain that explores these concepts individually ( Koehler et al., 2013). For example, a teacher masters the chemistry topic (e.g. acids and bases), its history and current state of research (CK), knows about the chemistry educational research on the topic and uses it in designing teaching (PCK), knows how the topic can be visualized using computers (TCK), is familiar with the possibilities and limitations of visualisations in teaching (TPK), and understands how learning is supported from both general (PK) and chemistry learning perspectives (PCK).

In chemistry education research, some of the uses of TPACK include analysing pedagogical models on how simulations can be used in teaching ( Khan, 2011), studying chemistry teachers' self-efficacy beliefs related to the use of certain technology and social media ( Blonder et al., 2013; Blonder & Rap, 2017), evaluating the effect of certain courses in pre-service teacher training ( Çalik, Özsevgeç, Ebenezer, Artun, & Küçük, 2014; Cetin-Dindar, Boz, Sonmez, & Celep, 2018), and mapping teachers' use of ICT in classroom practices in order to design accurate in-service ICT training programs ( Helppolainen & Aksela, 2015).

According to Koehler et al. (2013), TPACK has been widely used in ICT-related learning environment designs. They evaluated 141 research articles and isolated three main approaches for developing TPACK, which are:

3.

Simultaneous development of PCK and TPACK: Teachers develop their teaching via iterative projects, which enable insights in pedagogy, technology, content, and their interaction at the same time. ( Koehler et al., 2013)

This context on how the TPACK framework is used was also applied in the current study. The three above mentioned approaches were used to evaluate the major TPACK design strategies implemented in earlier 3D printing literature. These are tightly connected with the other goal of this research, which was to analyse the motivation for applying 3D printing in chemistry education. The hypothesis was that adopting new technology has some educational objective that attempts to change the current situation.

TPACK model has also been criticized. E.g. Graham (2011) discusses that the diversity and inaccuracy of definitions for different knowledge components makes the model unclear and unpractical (see also Cox, 2008; Willermark, 2018 for more critical views). Even though the critics, the extensive use of TPACK and chemistry educational research examples makes us confident that TPACK is a suitable tool for systematically reviewing and understanding the previous work done in the field. This will support designing the future 3D printing research in chemistry education.

Methods

This research was executed as a systematic literature analysis, which was chosen because it is an appropriate strategy for achieving the goal of including all relevant articles in the analysis ( Nightingale, 2009). The study was conducted by answering the following research questions derived from the research objectives:

Research data was selected via relevance sampling ( Krippendorff, 2004, pp. 118-121). We included all relevant peer-reviewed articles discussing 3D printing in chemistry education. The data was gathered from the most established educational research article databases like DOAJ, ERIC, Google Scholar, and Scopus ( Table 1). In total, 47 peer reviewed articles were retrieved in the information retrieval process (until March 25, 2019). Conference papers, book chapters, letters, etc. were excluded from the data because of the uncertainty of the peer-reviewing process.

RQ1 was answered via a general overview of the published literature. RQ2 and RQ3 were answered by analysing articles with qualitative content analysis, which is an analysis method that enables systematic and replicable literature analysis. We used two kinds of qualitative analysis methods, depending on the analysis needs. The first was a deductive theory-based approach ( Krippendorff, 2004), which was applied in situations where we needed to analyse how different TPACK components (PCK, TCK or TPK) appeared in the design process. The other approach was an inductive content-based approach, which was used in cases where the goal was to derive new classifications from the literature.

In general, the analysis processes were carried out through the following steps (see comparison of inductive and deductive approaches in Table 2):

When suitable, reliability of the analysis was evaluated using Cohen's kappa inter-rater reliability test. Cohen's kappa is a statistic evaluation model that illustrates the degree of agreement among raters. A kappa value greater than 0.80 indicates a strong level of agreement ( McHugh, 2012).

Results

Overview of earlier work (RQ1)

The total amount of articles published on 3D printing in the field of chemistry education was 47. The majority of the academic discussion appeared in the Journal of Chemistry Education (37 articles). The first publication was in 2010; since then, the number of publications has increased steadily ( Figure 2).

Ten of the 47 articles were classified as research articles, which were defined as articles that included some empirical section that studied, for example, students' perceptions or measured physical models' effect on learning. The remaining 37 articles focused on developing printing methodologies, analysing safety issues, developing pedagogical models and meaningful printing contexts (e.g. chemistry concepts and laboratory instruments) (see Table 3). Almost all of the articles discussed printing methodologies to some extent, but only eight articles focused exclusively on it. Presentation of suitable printing contexts for chemistry education was the biggest objective category identified from earlier publications. Altogether, 28 articles focused on describing which chemistry topics or laboratory instruments could benefit from 3D printing. All articles analysed in the research, as well as their full categorisation, are listed in Appendix 1.

Article category

Frequency

Percentage

A total of 29 different chemistry contexts for 3D printing were identified. Through content-based analysis, these contexts were classified into three categories: (1) physical molecular models (n = 13), (2) physical models (n = 7) and (3) laboratory instrument-related printing (n = 9).

TPACK design strategies (RQ2)

Here we discuss TPACK design strategies that have been implemented in developing TPACK through 3D printing. First, we present an overview of all the design processes identified. Next, different variations of TPACK processes are explored by reviewing one process at a time. Notably, design processes were not analysed from the ten research articles. The findings related to earlier research are discussed in the next chapter by answering the third research question. Because of this delimitation, the total amount of analysed processes was 37.

Our theory-based content analysis identified three types of design strategies, of which two (processes 1 and 3) were similar to those presented by Koehler et al. (2013) (see Table 4). The majority of the articles (n = 18/37) approached the development of 3D printing based TPACK by identifying challenges and possibilities that current pedagogical solutions possess (PCK). After analysing pedagogical needs, 3D printing was used for solving the identified challenges (TCK). The second most common approach for TPACK was developing PCK and TCK simultaneously (n = 11/37). A case example of this approach was developing a pedagogical model that integrates 3D printing in teaching as a working method for chemistry learning. In this model students learn chemistry through 3D printing activities. The third approach for TPACK identified in this study was TCK + PCK (n = 8/37). In this approach the challenges and possibilities were analysed through chemical technology knowledge (e.g. laboratory instruments or 3D printing) and pedagogical solutions were developed for applying this knowledge. We did not find any approaches that would match the description of Koehler et al. (2013) design strategy number 2 (TPK to TPACK). According to the inter-rater reliability test, these results are reliable. We also found that the strength of agreement among two raters was very strong (k = 0.82).

TPACK design process

Frequency

Percentage

Design process 1: PCK + TCK to TPACK

PCK-based reasoning was the most used design strategy for TPACK. Through content-based analysis, we identified several PCK-related challenges that authors used for rationalising the use of 3D printing in chemistry education. Such arguments include descriptions of challenges in teaching or learning, lack or limitations of current molecular model solutions (e.g. is the model qualitative or based on calculations), or high cost of suitable tangible models. In addition to these challenges, the possibilities that physical models offer for chemistry learning were also mentioned ( Table 5). 3D printing was used as a method for designing and manufacturing improved physical models and molecular models (TCK) that could serve as a solution for the abovementioned PCK-based challenges and possibilities. These improvements focused on, for example, the development of more accurate data-based molecular models, or printing models that would be impossible to construct using traditional plastic models. The TPACK goal of this approach was to identify chemistry contexts that would benefit from 3D printing, and develop pedagogical models or use cases for these improved physical models.

PCK

Example statement from literature

High cost of suitable molecular models
"Crystal-structure models are not as standardized as molecular models, and many creative and cheap ways to represent them have been presented.

....

Wood models continue to be the most used in the classroom. However, when these have to be replaced due to wear and tear, an expensive new copy has to be ordered from a skilled carpenter. Commercial wooden kits are available, but they are rare and expensive; the German company Krantz is one of the few suppliers. Low cost alternatives have been presented using paper 8, 9 though these have a lower durability.

...

Limitations of current molecular models
"An important limitation of widely used student molecular model sets, however, is that they do not represent π bonding with p orbital isosurfaces.

....

Design process 4: TCK + PCK to TPACK

All articles in which the authors rationalised 3D printing through TCK-based arguments were classified into this category. These arguments include challenges in current solutions (e.g. quality of models), processes (e.g. high cost, difficulties in the process, or lack of files in the databases), or chemistry knowledge about the possibility to customise laboratory instruments (technology) ( Table 6). From a TPACK point of view, 3D printing was used as a method for manufacturing parts for instrument customisation, or the design was focused on developing 3D printing processes that are more suitable for educational purposes.

TCK

Example statement from literature

Possibilities for laboratory instrument customisation

"However, the technology reported here is unique in that the measurement device is engineered to allow direct quantitation of the free ligand with the use of a plate reader, shown in Figure 1. The direct quantitation feature of the device allows the typical time-consuming experiment (approximately 14 h) to be set up in a single 1 h time period and left unattended until the next day." ( Pinger, Castiaux, Speed, & Spence, 2018)

The majority of the printing methodology articles were assigned to this category. Many evaluated the existing technologies and designed novel technically easy printing processes for all printer types, including low-cost printers. Rossi, Benaglia, Brenna, Porta, and Orlandi (2015) developed a simple procedure for converting protein data bank files into stereolithography with accurate geometry via the Virtual Molecular Dynamic software. Jones and Spencer (2018) describe how the National Institutes of Health 3D Print Exchange website can be used to make the 3D printing process less technical. The service allows the user to upload, edit, and share 3D files that are not ready for printing, and download them as 3D printable files - even when users do not have previous experience in 3D printing. Their objective was to develop a printing process that does not require the use of multiple software programmes, and to encourage teachers and students with low technological skills to use 3D printing.

Some articles describe new software that have been developed for supporting 3D printing. Scalfani et al. (2016) introduced a Jmol script that enables conversion of crystal structures into 3D printable files. Paukstelis (2018) developed MolPrint3D add on for the Blender software that allows splitting molecules into smaller fragments. MolPrint3D adds pins and holes between fragments for assembling. These junction points reduce the need for support structures, which enables printing of even large macromolecular structures as ball-and-stick models. The focus of this research was to improve the quality of currently printed molecular models.

Design process 3: PCK/TCK + PCK/TCK/TPK to TPACK

This was the most comprehensive TPACK development category, in which we classified all articles that described activities for supporting students' engagement. Articles placed in this category approached TPACK design through PCK or TCK arguments, but they differ from the previous categories because students have an active role in 3D printing. Students will learn chemistry through 3D printing, and vice versa. The central TPACK objective of this category was to develop pedagogical models for integrating 3D printing in chemistry education. For example, Fedick, Schrader, Ayrton, Pulliam, and Cooks (2019) integrated student centered 3D printing activities in learning process analytical technologies (PAT); Dean, Ewan, and McIndoe (2016) developed a new molecular modelling method using hand-held 3D printing pens; and Kosenkov, Shaw, Zuczek, and Kholod (2016) developed a project-based learning approach for learning chemistry through novel technologies ( Table 7).

TPACK

Example statement from literature

3D printing in chemistry education research (RQ3)

The research articles analysed in our study included some empirical section focusing on chemistry educational research, except one article that focused on measuring ultrafine particles (UFPs) and volatile organic compounds (VOCs) emitted from 3D printing processes ( Bharti & Singh, 2017). The quality of research, however, was not evaluated. Seven of ten research articles discussed topic-specific learning barriers and alternative concepts in theoretical framework. 3D printing was used for producing instructional materials that could support challenges reported in earlier research. Research settings were designed for gathering students' perceptions on learning via physical models ( De Cataldo, Griffith, & Fogarty, 2018; Dean, Ewan, Braden, & McIndoe, 2019; Hall et al., 2017; Smiar & Mendez, 2016) or measuring their learning effects ( Babilonia-Rosa, Kuo, & Oliver-Hoyo, 2018; Cooper & Oliver-Hoyo, 2017; Wuttisela, 2017). Fourches and Feducia (2019) analysed students' perceptions towards 3D printing as a work method. In addition to these, Wedler et al. (2012) developed 3D printing supported chemistry learning methods for blind and visually impaired students, and probed their perceptions towards a developed learning method (see Table 8).

Three articles concentrated fully on research. Babilonia-Rosa et al. (2018) used printed physical models for probing knowledge integration (integrating new ideas to existing cognitive structure) in biochemistry. Using physical models as instructional materials and drawings as a working method, their research - conducted in an introductory biochemistry course for nonmajors (n = 53) - produced new knowledge on the mechanisms of knowledge integration. Cooper and Oliver-Hoyo (2017) also worked in an introductory level biochemistry course (n = 131). They designed and printed physical models that visualised electrostatics and noncovalent interactions, and their effect on macromolecular structures. They found that the use of physical tangible models can reduce the barriers of understanding and help focus on the important concepts that cause the properties. Wuttisela (2017) developed an assessment tool via 3D printing for measuring pharmacy students' (n = 29) understanding of the valence shell electron pair repulsion theory.

Four articles were partly research articles. They addressed the printing process and included a small case study on perceptions or effect on learning. Smiar and Mendez (2016) printed interactive physical molecular models (e.g. hybridisation) and atom models which were well received by students (n = 26) in a higher education introductory chemistry course. De Cataldo et al. (2018) also worked with hybridisation with introductory level chemistry students. According to their survey, students (n = 34) experienced that physical models supported their understanding of atomic and hybrid orbitals. Hall et al. (2017) evaluated pharmacy students' (n = 24) perceptions and educational benefits of 3D printed molecular models in learning drug receptor and enzyme interactions. They reported that over 90 % of the pharmacy students found that the physical models improved their engaging and learning outcomes. Fourches and Feducia (2019) studied if 3D printing is a suitable work method for student-centred activities. They reported that students enjoyed learning organic chemistry through 3D printing and it supported their engagement to the course.

Starting knowledge

The role of 3D printing

Obtained knowledge

Where to apply in chemistry education?

UFPs and VOCs released from 3D printing

Source of UPFs and VOCs

Knowledge for designing safety recommendations ( Bharti & Singh, 2017)

Developing safety recommendations for 3D printing

- Physical models' possibilities in supporting chemistry learning

- Learning challenges of some chemistry topic

- Challenges of printing processes (e.g. cost and difficulty)

Printing research instruments/models/molecular models

Knowledge of physical models' effect into knowledge integration ( Babilonia-Rosa et al., 2018)

Developing pedagogical models for teaching and learning via physical models

Knowledge of physical models' effect on learning chemistry topics ( Cooper & Oliver-Hoyo, 2017; Hall et al., 2017)

Knowledge of physical models' effect on reducing misconceptions ( Wuttisela, 2017)

Knowledge of students' perceptions towards physical models ( De Cataldo et al., 2018; Dean et al., 2019; Smiar & Mendez, 2016)

Integrating 3D printing in learning process

Knowledge of how printing and physical models' effect on blind and visually impaired students learning ( Wedler et al., 2012)

Develop chemistry teaching and learning of blind and visually impaired students via 3D printing

Knowledge of students' perceptions towards 3D printing ( Fourches & Feducia, 2019)

Develop 3D printing supported learning processes

Safety issues related to 3D printing have received little attention in earlier publications. Almost all analysed articles with hands-on activities included some short safety description, but only one article addressed the topic of safety on a comprehensive level. According to Bharti and Singh (2017), there are significant 3D printing-related safety issues to consider. For example, the two most commonly printed polymers are polylactic acid and acrylonitrile butadiene styrene. These polymers melt during the printing process, which emits particles of UPFs less than 100 nm wide, VOCs and some other potentially carcinogenic compounds like aldehydes and phthalates ( Figure 3) ( Azimi, Zhao, Pouzet, Crain, & Stephens, 2016; Kim et al., 2015).

The emission rates of UFPs, VOCs and other compounds have been analysed in a few studies. Kim et al. (2015) found that ABS filaments have higher UPF and VOC emissions than PLA filaments. Azimi et al. (2016) measured the concentration of emissions from multiple commercially available filament desktop printers, and observed a significant increase in UPFs and VOCs (especially styrene, which is classified as a possible carcinogen for humans) in the printing space. Bharti and Singh (2017) measured the number of UPFs in libraries and makerspaces. Importantly, they observed a significant increase in UPF levels even 24 h after the printers had been shut down. Because of this, 3D printers should only be used in a well-ventilated space or a fume hood. The authors emphasise that avoiding inhalation of UPFs and VOCs must be taken into account during 3D printing, and they have suggested pragmatic safety instructions that are well applicable in chemistry education ( Bharti & Singh, 2017).

Conclusions

3D printing is a rapidly growing industry ( Hart, 2017a, Hart), however it still remains a niche topic in chemistry education. Only 47 peer-reviewed articles have been published about 3D printing in chemistry education, only ten of which are research papers. Most of these earlier studies have focused on finding relevant chemistry topics that would benefit from 3D printing (see Table 9). Because of this, the most common way to design TPACK was to analyse PCK-based chemistry educational challenges ( Koehler et al., 2013) that could be solved via designing and printing improved physical models (TCK). These improvements were rationalised, for example, through the need for more accurate models or lack of available solutions. For example, 3D printing enables data-based model design (e.g. Carroll & Blauch, 2017) and printing complex structures that are not possible to construct with traditional plastic models (e.g. Casas & Estop, 2015; Lolur & Dawes, 2014).

Another major subject-specific approach was to first analyse the chemistry technological challenges (TCK) and then use 3D printing to solve them, with some educational objective (PCK). This approach was not present in Koehler et al. (2013) TPACK design strategy classification. One possible reason for this could be that their data did not include any subject-specific TPACK development projects.

Only 11 articles described pedagogical models where students had an active role in 3D printing. Twenty-nine of the studied articles reported different PCK- or TCK-based challenges for which solutions were found through 3D printing. These articles offer a high pedagogical value from a chemistry context (TCK) perspective, but the contributions for comprehensive development of TPACK are quite limited ( Koehler & Mishra 2005; 2009; Koehler et al., 2013; Mishra & Koehler, 2006). Hence, due to this clear knowledge gap, there is a great need for developing student centred 3D printing activities for chemistry education. This result is in line with earlier 3D printing studies carried out from a general educational perspective. For example, it has been found that 3D printing is often used to support traditional teaching methods (see Nemorin & Selwyn, 2017).

In conclusion, exploiting the potential of 3D printing in chemistry education could be much more holistic. Suitable chemistry contexts for 3D printing are already well known, as researchers have been mapping these out for almost a decade. In chemistry education research, however, the use of 3D printing has been rare. Thus far, it has mainly been used as a tool for manufacturing research instruments for studying students' perceptions towards physical models or their effect on learning (e.g. Wuttisela, 2017). There is some evidence that 3D printing is suitable for student-centred activities for supporting the engagement in studies ( Fourches & Feducia, 2019), but in order to develop more versatile and holistic models for integrating 3D printing in chemistry education, it would be crucial to study whether 3D printing is a relevant work method for future chemistry teachers'. Relevance should be analysed from several perspectives, for example, possibilities for learning, engagement, self-confidence, professional development etc. and also its societal relevance (see Stuckey, Hofstein, Mamlok-Naaman, & Eilks, 2013). Based on this knowledge, it would be easier to design research-based 3D printing learning environments relevant for chemistry education. And it is important to remember that when new pedagogical models and learning environments are designed, safety details must be taken account for because of the large amount of potentially carcinogenic UFPs and VOCs that 3D printing releases ( Bharti & Singh, 2017).

# data[].attributes.attachment_link.title
A systematic review of 3D printing in chemistry education - analysis of earlier research and educational use through technological pedagogical content knowledge framework

# data[].attributes.attachment_link.description
The focus of this systematic literature analysis is to provide a comprehensive review of earlier research on the utilisation of 3D printers in chemistry education. The objective is to offer research-based knowledge for developing chemistry education through following research questions: what kind of work has been done in the field of 3D printing in chemistry education; what kind of design strategies have been implemented; how 3D printing has been used in chemistry education research.

# data[].attributes.headline
เรื่อง สารละลาย หัวข

# data[].attributes.body
เรื่อง สารละลาย หัวข้อ สมบัติบาประการของสารละลาย

# data[].attributes.attachment_link.title
แผนการจัดการเรียนรู้สมบัติสารละลาย (แผนหน้าเดียว)

# data[].attributes.headline
แผนหน้าเดียว พราวฝัน 160 เคมีกับการแก้ปัญหา

# data[].attributes.subject
แผนหน้าเดียว พราวฝัน 160 เคมีกับการแก้ปัญหา

# data[].attributes.attachment_link.title
แผนหน้าเดียวเคมีกับการแก้ไขปัญหา

# data[].attributes.headline
เบญญาภา การแพร่ของแก๊ส(เซนเซอร์วัดแก๊ส)

# data[].attributes.subject
เบญญาภา การแพร่ของแก๊ส(เซนเซอร์วัดแก๊ส)

# data[].attributes.attachment_link.title
แผนหน้าเดียว_เบญญาภา

# data[].attributes.headline
แผนหน้าเดียว วิทย์กายภาพ ม.5

# data[].attributes.subject
แผนหน้าเดียว วิทย์กายภาพ ม.5

# data[].attributes.body
ประเด็นท้าทาย : การทดลองปัจจัยที่มีผลต่ออัตราการเกิดปฏิกิริยาเคมี

# data[].attributes.attachment_link.title
 แผนหน้าเดียว ม.5 วิทย์กายภาพ_ชนิสรา

# data[].attributes.headline
 ชัชวาล ประเด็นเครื่องปริ้น3 มิติ

# data[].attributes.subject
 ชัชวาล ประเด็นเครื่องปริ้น3 มิติ

# data[].attributes.body
ประเด็น เครื่

# data[].attributes.attachment_link.title
แผนหน้าเดียว-รูปร่างโมเลกุลโคเวเลนต์

# data[].attributes.headline
น้องเฮเลน TH

# data[].attributes.subject
น้องเฮเลน TH

# data[].attributes.body
https://so04.tci-thaijo.org/index.php/JSSE/article/download/194898/135527/

# data[].attributes.headline
น้องเฮเลน ENG 

# data[].attributes.subject
น้องเฮเลน ENG 

# data[].attributes.body
https://www.degruyter.com/document/doi/10.1515/cti-2019-0005/html

# data[].attributes.attachment_link.readable_text
Introduction

Additive manufacturing, commonly known as 3D printing, refers to technologies that build 3D objects by adding material layer by layer. Added material can be, for example, plastic or metal; the former is the most used in chemistry education ( Bharti & Singh, 2017). Additive manufacturing has many advantages compared to traditional processes. Firstly, in many cases it is easier to produce complex artefacts additively than subtractive (e.g. CNC machining) ( Jamie, 2018; Lolur & Dawes, 2014). Secondly - and most importantly - the waste of raw material is minimal, supporting environmentally friendly and sustainable chemistry thinking ( Andraos & Dicks, 2012).

Additive manufacturing is a rapidly growing field. Although currently it is only a marginal part of the entire manufacturing industry, it is nevertheless considered a common production method alongside traditional methods ( Long, 2018). It is already an essential technique for digital manufacturing and home fabrication, and the general consensus is that 3D printing will be one of the next major technological revolutions ( Rayna & Striukova, 2016).

According to Hart (2017a), fast growth has created a skill gap in additive manufacturing. The rising industry is struggling to find people skilled in 3D printing and is looking for support from the education sector. The additive manufacturing industry has a great need for experts; the education sector has the possibility and responsibility to respond to this demand ( Hart, 2017a, Hart). This need has been recognized in schools, and enthusiastic teachers worldwide are developing pedagogical models on the integration of 3D printing in school curricula. At the same time, the price of 3D printers has decreased, enabling more schools to purchase the technology ( Litts, 2015). Expectations are high - teachers using 3D printing have reported that it supports the development of multiple skills relevant for the 21 st century, such as 3D modelling, creativity, and important learning skills (e.g. critical thinking, problem-solving and self-directed learning) ( Trust & Maloy, 2017). Enthusiasm about 3D printing as an educational innovation is massive, however Nemorin and Selwyn (2017) argued that integrating 3D printing in a learning context is a challenging design task for the learning environment. Hence, it is important to understand how this new technology is being used in schools, and if it represents a new innovative form of education. According to their research, there were many cases where such new technology was used to support the traditional behaviourist way of teaching and learning. Nemorin and Selwyn (2017) research findings, however, conflict with the hopes that are set for educational 3D printing ( Trust & Maloy, 2017).

Nemorin and Selwyn (2017) suggest that the pedagogical use of 3D printing might change over time, after more teachers and students become familiar with the makerspace culture. It could change the working culture around 3D printing in formal education, and 3D printing could also serve as one model for informal out-of-school learning. However, the cultural change will take time, yet the need for skilled additive manufacturers is immediate, making this topic of outmost importance in current chemistry education ( Nemorin & Selwyn, 2017).

It has been proposed that "3D printing offers nearly unlimited potential for chemical educators" ( Davis, Jones, Thiel, & Pauls, 2018). Although several articles have been published on this topic, the current state of research and pedagogical development remains unclear. The goal of the present article is to evaluate this potential via a comprehensive review of published literature on 3D printing. We approach this goal by analysing the type of publications that have been published, the reported motivation for 3D printing, and the type of learning environment design strategies that have been used. The analysis of strategies is carried out using a Technological Pedagogical Content Knowledge (TPACK) framework, which is widely used to understand the possibilities and challenges related to the pedagogical use of technology in general ( Koehler, Mishra, & Cain, 2013; Mishra & Koehler, 2006). This review summarizes the current state of 3D printing in chemistry education, which in turn should enable the development of chemistry teacher education and research that comprehensively accounts for the earlier research done in this field.

Technological pedagogical content knowledge

TPACK is a widely adopted knowledge framework that illustrates the different types of knowledge that teachers need to master for the successful use of technology in their teaching ( Koehler & Mishra 2005; 2009; Mishra & Koehler, 2006). Since its publication in 2005, there are over 900 published TPACK-related research articles ( TPACK.org, 2018). It was originally developed to respond to the criticism concerning the lack of theoretical grounding for educational technology ( Koehler & Mishra, 2005). From historical perspective, TPACK is an iteration of Shulman's Pedagogical Content Knowledge (PCK) model ( Shulman 1986; 1987), which emphasized the important interaction between pedagogical knowledge and content knowledge. PCK model was developed before the age of modern educational technology, which inspired Mishra and Koehler to redesign Shulman's ideas with the aim of explaining how teachers' understanding of how technology and PCK can interact, resulting in the successful integration of education and technology ( Koehler & Mishra, 2005; Mishra & Koehler, 2006).

The TPACK framework consists of several knowledge domains ( Figure 1). The three main components of teachers' knowledge are pedagogical knowledge (PK), content knowledge (CK), and technological knowledge (TK) ( Koehler & Mishra, 2005; Mishra & Koehler, 2006).

-

TK covers the knowledge about how to use technology (e.g. devices, software, communication tools) to support work and everyday life. TK must be constantly developed because of the rapid changes in information and communication technology (ICT) ( Koehler & Mishra, 2009; Koehler et al., 2013).

The interaction of these components forms three complex knowledge categories: pedagogical content knowledge (PCK), technological content knowledge (TCK), and technological pedagogical knowledge (TPK) ( Koehler & Mishra, 2005; Mishra & Koehler, 2006).

-

TPK is the understanding of the possibilities that technology can offer for learning. TPK does not have a subject-specific (CK) perspective ( Koehler & Mishra, 2009; Koehler et al., 2013).

TPACK is a knowledge domain that emerges from the interaction of content, pedagogy, and technology knowledge in the chosen context. It is a more versatile understanding of possibilities and challenges of ICT in teaching and learning than any other knowledge domain that explores these concepts individually ( Koehler et al., 2013). For example, a teacher masters the chemistry topic (e.g. acids and bases), its history and current state of research (CK), knows about the chemistry educational research on the topic and uses it in designing teaching (PCK), knows how the topic can be visualized using computers (TCK), is familiar with the possibilities and limitations of visualisations in teaching (TPK), and understands how learning is supported from both general (PK) and chemistry learning perspectives (PCK).

In chemistry education research, some of the uses of TPACK include analysing pedagogical models on how simulations can be used in teaching ( Khan, 2011), studying chemistry teachers' self-efficacy beliefs related to the use of certain technology and social media ( Blonder et al., 2013; Blonder & Rap, 2017), evaluating the effect of certain courses in pre-service teacher training ( Çalik, Özsevgeç, Ebenezer, Artun, & Küçük, 2014; Cetin-Dindar, Boz, Sonmez, & Celep, 2018), and mapping teachers' use of ICT in classroom practices in order to design accurate in-service ICT training programs ( Helppolainen & Aksela, 2015).

According to Koehler et al. (2013), TPACK has been widely used in ICT-related learning environment designs. They evaluated 141 research articles and isolated three main approaches for developing TPACK, which are:

3.

Simultaneous development of PCK and TPACK: Teachers develop their teaching via iterative projects, which enable insights in pedagogy, technology, content, and their interaction at the same time. ( Koehler et al., 2013)

This context on how the TPACK framework is used was also applied in the current study. The three above mentioned approaches were used to evaluate the major TPACK design strategies implemented in earlier 3D printing literature. These are tightly connected with the other goal of this research, which was to analyse the motivation for applying 3D printing in chemistry education. The hypothesis was that adopting new technology has some educational objective that attempts to change the current situation.

TPACK model has also been criticized. E.g. Graham (2011) discusses that the diversity and inaccuracy of definitions for different knowledge components makes the model unclear and unpractical (see also Cox, 2008; Willermark, 2018 for more critical views). Even though the critics, the extensive use of TPACK and chemistry educational research examples makes us confident that TPACK is a suitable tool for systematically reviewing and understanding the previous work done in the field. This will support designing the future 3D printing research in chemistry education.

Methods

This research was executed as a systematic literature analysis, which was chosen because it is an appropriate strategy for achieving the goal of including all relevant articles in the analysis ( Nightingale, 2009). The study was conducted by answering the following research questions derived from the research objectives:

Research data was selected via relevance sampling ( Krippendorff, 2004, pp. 118-121). We included all relevant peer-reviewed articles discussing 3D printing in chemistry education. The data was gathered from the most established educational research article databases like DOAJ, ERIC, Google Scholar, and Scopus ( Table 1). In total, 47 peer reviewed articles were retrieved in the information retrieval process (until March 25, 2019). Conference papers, book chapters, letters, etc. were excluded from the data because of the uncertainty of the peer-reviewing process.

RQ1 was answered via a general overview of the published literature. RQ2 and RQ3 were answered by analysing articles with qualitative content analysis, which is an analysis method that enables systematic and replicable literature analysis. We used two kinds of qualitative analysis methods, depending on the analysis needs. The first was a deductive theory-based approach ( Krippendorff, 2004), which was applied in situations where we needed to analyse how different TPACK components (PCK, TCK or TPK) appeared in the design process. The other approach was an inductive content-based approach, which was used in cases where the goal was to derive new classifications from the literature.

In general, the analysis processes were carried out through the following steps (see comparison of inductive and deductive approaches in Table 2):

When suitable, reliability of the analysis was evaluated using Cohen's kappa inter-rater reliability test. Cohen's kappa is a statistic evaluation model that illustrates the degree of agreement among raters. A kappa value greater than 0.80 indicates a strong level of agreement ( McHugh, 2012).

Results

Overview of earlier work (RQ1)

The total amount of articles published on 3D printing in the field of chemistry education was 47. The majority of the academic discussion appeared in the Journal of Chemistry Education (37 articles). The first publication was in 2010; since then, the number of publications has increased steadily ( Figure 2).

Ten of the 47 articles were classified as research articles, which were defined as articles that included some empirical section that studied, for example, students' perceptions or measured physical models' effect on learning. The remaining 37 articles focused on developing printing methodologies, analysing safety issues, developing pedagogical models and meaningful printing contexts (e.g. chemistry concepts and laboratory instruments) (see Table 3). Almost all of the articles discussed printing methodologies to some extent, but only eight articles focused exclusively on it. Presentation of suitable printing contexts for chemistry education was the biggest objective category identified from earlier publications. Altogether, 28 articles focused on describing which chemistry topics or laboratory instruments could benefit from 3D printing. All articles analysed in the research, as well as their full categorisation, are listed in Appendix 1.

Article category

Frequency

Percentage

A total of 29 different chemistry contexts for 3D printing were identified. Through content-based analysis, these contexts were classified into three categories: (1) physical molecular models (n = 13), (2) physical models (n = 7) and (3) laboratory instrument-related printing (n = 9).

TPACK design strategies (RQ2)

Here we discuss TPACK design strategies that have been implemented in developing TPACK through 3D printing. First, we present an overview of all the design processes identified. Next, different variations of TPACK processes are explored by reviewing one process at a time. Notably, design processes were not analysed from the ten research articles. The findings related to earlier research are discussed in the next chapter by answering the third research question. Because of this delimitation, the total amount of analysed processes was 37.

Our theory-based content analysis identified three types of design strategies, of which two (processes 1 and 3) were similar to those presented by Koehler et al. (2013) (see Table 4). The majority of the articles (n = 18/37) approached the development of 3D printing based TPACK by identifying challenges and possibilities that current pedagogical solutions possess (PCK). After analysing pedagogical needs, 3D printing was used for solving the identified challenges (TCK). The second most common approach for TPACK was developing PCK and TCK simultaneously (n = 11/37). A case example of this approach was developing a pedagogical model that integrates 3D printing in teaching as a working method for chemistry learning. In this model students learn chemistry through 3D printing activities. The third approach for TPACK identified in this study was TCK + PCK (n = 8/37). In this approach the challenges and possibilities were analysed through chemical technology knowledge (e.g. laboratory instruments or 3D printing) and pedagogical solutions were developed for applying this knowledge. We did not find any approaches that would match the description of Koehler et al. (2013) design strategy number 2 (TPK to TPACK). According to the inter-rater reliability test, these results are reliable. We also found that the strength of agreement among two raters was very strong (k = 0.82).

TPACK design process

Frequency

Percentage

Design process 1: PCK + TCK to TPACK

PCK-based reasoning was the most used design strategy for TPACK. Through content-based analysis, we identified several PCK-related challenges that authors used for rationalising the use of 3D printing in chemistry education. Such arguments include descriptions of challenges in teaching or learning, lack or limitations of current molecular model solutions (e.g. is the model qualitative or based on calculations), or high cost of suitable tangible models. In addition to these challenges, the possibilities that physical models offer for chemistry learning were also mentioned ( Table 5). 3D printing was used as a method for designing and manufacturing improved physical models and molecular models (TCK) that could serve as a solution for the abovementioned PCK-based challenges and possibilities. These improvements focused on, for example, the development of more accurate data-based molecular models, or printing models that would be impossible to construct using traditional plastic models. The TPACK goal of this approach was to identify chemistry contexts that would benefit from 3D printing, and develop pedagogical models or use cases for these improved physical models.

PCK

Example statement from literature

High cost of suitable molecular models
"Crystal-structure models are not as standardized as molecular models, and many creative and cheap ways to represent them have been presented.

....

Wood models continue to be the most used in the classroom. However, when these have to be replaced due to wear and tear, an expensive new copy has to be ordered from a skilled carpenter. Commercial wooden kits are available, but they are rare and expensive; the German company Krantz is one of the few suppliers. Low cost alternatives have been presented using paper 8, 9 though these have a lower durability.

...

Limitations of current molecular models
"An important limitation of widely used student molecular model sets, however, is that they do not represent π bonding with p orbital isosurfaces.

....

Design process 4: TCK + PCK to TPACK

All articles in which the authors rationalised 3D printing through TCK-based arguments were classified into this category. These arguments include challenges in current solutions (e.g. quality of models), processes (e.g. high cost, difficulties in the process, or lack of files in the databases), or chemistry knowledge about the possibility to customise laboratory instruments (technology) ( Table 6). From a TPACK point of view, 3D printing was used as a method for manufacturing parts for instrument customisation, or the design was focused on developing 3D printing processes that are more suitable for educational purposes.

TCK

Example statement from literature

Possibilities for laboratory instrument customisation

"However, the technology reported here is unique in that the measurement device is engineered to allow direct quantitation of the free ligand with the use of a plate reader, shown in Figure 1. The direct quantitation feature of the device allows the typical time-consuming experiment (approximately 14 h) to be set up in a single 1 h time period and left unattended until the next day." ( Pinger, Castiaux, Speed, & Spence, 2018)

The majority of the printing methodology articles were assigned to this category. Many evaluated the existing technologies and designed novel technically easy printing processes for all printer types, including low-cost printers. Rossi, Benaglia, Brenna, Porta, and Orlandi (2015) developed a simple procedure for converting protein data bank files into stereolithography with accurate geometry via the Virtual Molecular Dynamic software. Jones and Spencer (2018) describe how the National Institutes of Health 3D Print Exchange website can be used to make the 3D printing process less technical. The service allows the user to upload, edit, and share 3D files that are not ready for printing, and download them as 3D printable files - even when users do not have previous experience in 3D printing. Their objective was to develop a printing process that does not require the use of multiple software programmes, and to encourage teachers and students with low technological skills to use 3D printing.

Some articles describe new software that have been developed for supporting 3D printing. Scalfani et al. (2016) introduced a Jmol script that enables conversion of crystal structures into 3D printable files. Paukstelis (2018) developed MolPrint3D add on for the Blender software that allows splitting molecules into smaller fragments. MolPrint3D adds pins and holes between fragments for assembling. These junction points reduce the need for support structures, which enables printing of even large macromolecular structures as ball-and-stick models. The focus of this research was to improve the quality of currently printed molecular models.

Design process 3: PCK/TCK + PCK/TCK/TPK to TPACK

This was the most comprehensive TPACK development category, in which we classified all articles that described activities for supporting students' engagement. Articles placed in this category approached TPACK design through PCK or TCK arguments, but they differ from the previous categories because students have an active role in 3D printing. Students will learn chemistry through 3D printing, and vice versa. The central TPACK objective of this category was to develop pedagogical models for integrating 3D printing in chemistry education. For example, Fedick, Schrader, Ayrton, Pulliam, and Cooks (2019) integrated student centered 3D printing activities in learning process analytical technologies (PAT); Dean, Ewan, and McIndoe (2016) developed a new molecular modelling method using hand-held 3D printing pens; and Kosenkov, Shaw, Zuczek, and Kholod (2016) developed a project-based learning approach for learning chemistry through novel technologies ( Table 7).

TPACK

Example statement from literature

3D printing in chemistry education research (RQ3)

The research articles analysed in our study included some empirical section focusing on chemistry educational research, except one article that focused on measuring ultrafine particles (UFPs) and volatile organic compounds (VOCs) emitted from 3D printing processes ( Bharti & Singh, 2017). The quality of research, however, was not evaluated. Seven of ten research articles discussed topic-specific learning barriers and alternative concepts in theoretical framework. 3D printing was used for producing instructional materials that could support challenges reported in earlier research. Research settings were designed for gathering students' perceptions on learning via physical models ( De Cataldo, Griffith, & Fogarty, 2018; Dean, Ewan, Braden, & McIndoe, 2019; Hall et al., 2017; Smiar & Mendez, 2016) or measuring their learning effects ( Babilonia-Rosa, Kuo, & Oliver-Hoyo, 2018; Cooper & Oliver-Hoyo, 2017; Wuttisela, 2017). Fourches and Feducia (2019) analysed students' perceptions towards 3D printing as a work method. In addition to these, Wedler et al. (2012) developed 3D printing supported chemistry learning methods for blind and visually impaired students, and probed their perceptions towards a developed learning method (see Table 8).

Three articles concentrated fully on research. Babilonia-Rosa et al. (2018) used printed physical models for probing knowledge integration (integrating new ideas to existing cognitive structure) in biochemistry. Using physical models as instructional materials and drawings as a working method, their research - conducted in an introductory biochemistry course for nonmajors (n = 53) - produced new knowledge on the mechanisms of knowledge integration. Cooper and Oliver-Hoyo (2017) also worked in an introductory level biochemistry course (n = 131). They designed and printed physical models that visualised electrostatics and noncovalent interactions, and their effect on macromolecular structures. They found that the use of physical tangible models can reduce the barriers of understanding and help focus on the important concepts that cause the properties. Wuttisela (2017) developed an assessment tool via 3D printing for measuring pharmacy students' (n = 29) understanding of the valence shell electron pair repulsion theory.

Four articles were partly research articles. They addressed the printing process and included a small case study on perceptions or effect on learning. Smiar and Mendez (2016) printed interactive physical molecular models (e.g. hybridisation) and atom models which were well received by students (n = 26) in a higher education introductory chemistry course. De Cataldo et al. (2018) also worked with hybridisation with introductory level chemistry students. According to their survey, students (n = 34) experienced that physical models supported their understanding of atomic and hybrid orbitals. Hall et al. (2017) evaluated pharmacy students' (n = 24) perceptions and educational benefits of 3D printed molecular models in learning drug receptor and enzyme interactions. They reported that over 90 % of the pharmacy students found that the physical models improved their engaging and learning outcomes. Fourches and Feducia (2019) studied if 3D printing is a suitable work method for student-centred activities. They reported that students enjoyed learning organic chemistry through 3D printing and it supported their engagement to the course.

Starting knowledge

The role of 3D printing

Obtained knowledge

Where to apply in chemistry education?

UFPs and VOCs released from 3D printing

Source of UPFs and VOCs

Knowledge for designing safety recommendations ( Bharti & Singh, 2017)

Developing safety recommendations for 3D printing

- Physical models' possibilities in supporting chemistry learning

- Learning challenges of some chemistry topic

- Challenges of printing processes (e.g. cost and difficulty)

Printing research instruments/models/molecular models

Knowledge of physical models' effect into knowledge integration ( Babilonia-Rosa et al., 2018)

Developing pedagogical models for teaching and learning via physical models

Knowledge of physical models' effect on learning chemistry topics ( Cooper & Oliver-Hoyo, 2017; Hall et al., 2017)

Knowledge of physical models' effect on reducing misconceptions ( Wuttisela, 2017)

Knowledge of students' perceptions towards physical models ( De Cataldo et al., 2018; Dean et al., 2019; Smiar & Mendez, 2016)

Integrating 3D printing in learning process

Knowledge of how printing and physical models' effect on blind and visually impaired students learning ( Wedler et al., 2012)

Develop chemistry teaching and learning of blind and visually impaired students via 3D printing

Knowledge of students' perceptions towards 3D printing ( Fourches & Feducia, 2019)

Develop 3D printing supported learning processes

Safety issues related to 3D printing have received little attention in earlier publications. Almost all analysed articles with hands-on activities included some short safety description, but only one article addressed the topic of safety on a comprehensive level. According to Bharti and Singh (2017), there are significant 3D printing-related safety issues to consider. For example, the two most commonly printed polymers are polylactic acid and acrylonitrile butadiene styrene. These polymers melt during the printing process, which emits particles of UPFs less than 100 nm wide, VOCs and some other potentially carcinogenic compounds like aldehydes and phthalates ( Figure 3) ( Azimi, Zhao, Pouzet, Crain, & Stephens, 2016; Kim et al., 2015).

The emission rates of UFPs, VOCs and other compounds have been analysed in a few studies. Kim et al. (2015) found that ABS filaments have higher UPF and VOC emissions than PLA filaments. Azimi et al. (2016) measured the concentration of emissions from multiple commercially available filament desktop printers, and observed a significant increase in UPFs and VOCs (especially styrene, which is classified as a possible carcinogen for humans) in the printing space. Bharti and Singh (2017) measured the number of UPFs in libraries and makerspaces. Importantly, they observed a significant increase in UPF levels even 24 h after the printers had been shut down. Because of this, 3D printers should only be used in a well-ventilated space or a fume hood. The authors emphasise that avoiding inhalation of UPFs and VOCs must be taken into account during 3D printing, and they have suggested pragmatic safety instructions that are well applicable in chemistry education ( Bharti & Singh, 2017).

Conclusions

3D printing is a rapidly growing industry ( Hart, 2017a, Hart), however it still remains a niche topic in chemistry education. Only 47 peer-reviewed articles have been published about 3D printing in chemistry education, only ten of which are research papers. Most of these earlier studies have focused on finding relevant chemistry topics that would benefit from 3D printing (see Table 9). Because of this, the most common way to design TPACK was to analyse PCK-based chemistry educational challenges ( Koehler et al., 2013) that could be solved via designing and printing improved physical models (TCK). These improvements were rationalised, for example, through the need for more accurate models or lack of available solutions. For example, 3D printing enables data-based model design (e.g. Carroll & Blauch, 2017) and printing complex structures that are not possible to construct with traditional plastic models (e.g. Casas & Estop, 2015; Lolur & Dawes, 2014).

Another major subject-specific approach was to first analyse the chemistry technological challenges (TCK) and then use 3D printing to solve them, with some educational objective (PCK). This approach was not present in Koehler et al. (2013) TPACK design strategy classification. One possible reason for this could be that their data did not include any subject-specific TPACK development projects.

Only 11 articles described pedagogical models where students had an active role in 3D printing. Twenty-nine of the studied articles reported different PCK- or TCK-based challenges for which solutions were found through 3D printing. These articles offer a high pedagogical value from a chemistry context (TCK) perspective, but the contributions for comprehensive development of TPACK are quite limited ( Koehler & Mishra 2005; 2009; Koehler et al., 2013; Mishra & Koehler, 2006). Hence, due to this clear knowledge gap, there is a great need for developing student centred 3D printing activities for chemistry education. This result is in line with earlier 3D printing studies carried out from a general educational perspective. For example, it has been found that 3D printing is often used to support traditional teaching methods (see Nemorin & Selwyn, 2017).

In conclusion, exploiting the potential of 3D printing in chemistry education could be much more holistic. Suitable chemistry contexts for 3D printing are already well known, as researchers have been mapping these out for almost a decade. In chemistry education research, however, the use of 3D printing has been rare. Thus far, it has mainly been used as a tool for manufacturing research instruments for studying students' perceptions towards physical models or their effect on learning (e.g. Wuttisela, 2017). There is some evidence that 3D printing is suitable for student-centred activities for supporting the engagement in studies ( Fourches & Feducia, 2019), but in order to develop more versatile and holistic models for integrating 3D printing in chemistry education, it would be crucial to study whether 3D printing is a relevant work method for future chemistry teachers'. Relevance should be analysed from several perspectives, for example, possibilities for learning, engagement, self-confidence, professional development etc. and also its societal relevance (see Stuckey, Hofstein, Mamlok-Naaman, & Eilks, 2013). Based on this knowledge, it would be easier to design research-based 3D printing learning environments relevant for chemistry education. And it is important to remember that when new pedagogical models and learning environments are designed, safety details must be taken account for because of the large amount of potentially carcinogenic UFPs and VOCs that 3D printing releases ( Bharti & Singh, 2017).

# data[].attributes.attachment_link.title
A systematic review of 3D printing in chemistry education - analysis of earlier research and educational use through technological pedagogical content knowledge framework

# data[].attributes.attachment_link.description
The focus of this systematic literature analysis is to provide a comprehensive review of earlier research on the utilisation of 3D printers in chemistry education. The objective is to offer research-based knowledge for developing chemistry education through following research questions: what kind of work has been done in the field of 3D printing in chemistry education; what kind of design strategies have been implemented; how 3D printing has been used in chemistry education research.

# data[].attributes.attachment_link.title
View of Designing TPACK-based course for preparing student teachers to teach science with technological pedagogical content knowledge

# data[].attributes.attachment_link.title
View of Handbook of Technological Pedagogical Content Knowledge (TPCK) for Education

# data[].attributes.attachment_link.description
Return to Article Details Handbook of Technological Pedagogical Content Knowledge (TPCK) for Education

# data[].attributes.body
https://iopscience.iop.org/article/10.1088/1742-6596/1521/4/042069/pdf

# data[].attributes.attachment_link.title
View of Development of STEM teacher's competencies measurement instrument using TPACK-STEM framework

# data[].attributes.attachment_link.description
Return to Article Details Development of STEM teacher's competencies measurement instrument using TPACK-STEM framework

# data[].attributes.body
http://nuir.lib.nu.ac.th/dspace/bitstream/123456789/1550/3/60030625.pdf

# data[].attributes.body
https://pubs.acs.org/doi/pdf/10.1021/acs.jchemed.0c01296

# data[].attributes.attachment_link.title
Developing Prospective Chemistry Teachers’ TPACK–A Comparison between Students of Two Different Universities and Expertise Levels Regarding Their TPACK Self-Efficacy, Attitude, and Lesson Planning Competence

# data[].attributes.attachment_link.description
The aim of this study was to investigate how to develop prospective chemistry teachers’ TPACK and thus qualify them for the effective use of educational technology in their future chemistry teaching. For this purpose, we developed and evaluated a university seminar for the professional development o…

# data[].attributes.body
https://so03.tci-thaijo.org/index.php/jrcd/article/view/93173/72996

# data[].attributes.attachment_link.title
View of การพัฒนาความรู้ในเนื้อหาผนวกวิธีสอนและเทคโนโลยีในการสอนวิทยาศาสตร์

# data[].attributes.attachment_link.description
Return to Article Details การพัฒนาความรู้ในเนื้อหาผนวกวิธีสอนและเทคโนโลยีในการสอนวิทยาศาสตร์

# data[].attributes.body
https://aip.scitation.org/doi/pdf/10.1063/5.0041804

# data[].attributes.attachment_link.description
Enter words / phrases / DOI / ISBN / authors / keywords / etc. SEARCH CITATION SEARCH

# data[].attributes.body
https://www.ejimed.com/download/effects-of-in-service-chemistry-teachers-technological-pedagogical-content-knowledge-on-students-9306.pdf

# data[].attributes.body
http://202.28.62.114/index.php/jre/article/download/11055/9170

# data[].attributes.body
https://fund.pkru.ac.th/storage/download/5ce5159a08813b0001fb6d62?sector=files2019&bucket=publish_paper&ver=0&sk=fe065788df418b7dae67425c11ec2e3a

# data[].attributes.body
https://studio.gometa.io/landing

# data[].attributes.attachment_link.description
Metaverse is the easiest way to create Augmented Reality experiences. No programming required.

# data[].attributes.attachment_link.title
ChemCollective HTML5 Virtual Lab Walkthrough

# data[].attributes.body
https://hololabchampions-schellgames-com.translate.goog/?_x_tr_sl=en&_x_tr_tl=th&_x_tr_hl=th&_x_tr_pto=sc

# data[].attributes.attachment_link.readable_text
Virtual Lab Practice, Real Lab Mastery

Grab your safety goggles and set out on a chemical-burning, liquid-stirring, camera-whirring competition in HoloLAB Champions.

Do you want this virtual lab in your classroom?

Check out the special deal for educators and access a Classroom Guide and other classroom resources.

For Educators

Formula For Success

You have been beamed into the HoloLAB. Now what? Put your lab skills to the test! If you can prove you are in your element, your brain will be immortalized for all eternity.

A Positively Charged Experience

Scoop, pour, and burn your way to mastery in the HoloLAB. Trophies, complete with a hologram of your brain, commemorate your achievements and adorn the immersive Hall of Brains.

What the Critics Are Saying

# data[].attributes.attachment_link.title
Hololab Champions | HoloLAB Champions | Schell Games

# data[].attributes.attachment_link.description
Grab your safety goggles and set out on a chemical-burning, liquid-stirring, camera-whirring competition in HoloLAB Champions. Check out the special deal for educators and access a Classroom Guide and other classroom resources. For Educators You have been beamed into the HoloLAB. Now what? Put your lab skills to the test!

# data[].attributes.body
https://store.steampowered.com/app/696760/HoloLAB_Champions/

# data[].attributes.attachment_link.readable_text
Reviews

"It's this sort of attention to detail that makes HoloLAB Champions a shining example of what can be achieved when mixing the worlds of VR entertainment and education together, thoroughly focusing your attention for the entire time."
4 out of 5 stars - VRFocus

"Although built as an educational tool, HoloLAB Champions also succeeds as a completely new way to experience practical science. It engages the mind as well as dexterity courtesy of challenging measurements, mixing puzzles, and mathematical elements, which should be fun for the science nerd in kids and adults."
90/100 Excellent - Gaming Trends

"...the game flowed pretty smoothly and kept me engaged enough to want to keep going. Which is great news for teachers and parents who are looking to inspire their students to learn. Or even for people who are simply looking to challenge their own knowledge in a game-like setting. HoloLAB Champions feels polished enough that it can be enjoyed by young and old alike."
8/10 - VRtheGamers

About This Game

HoloLAB Champions is a virtual reality chemistry game show, where you complete lab experiments to become a Champion of lab practice. Interact with equipment and materials that you'd find in an actual lab. You must finish your experiments safely and accurately to earn points for entrance into the Hall of Brains. Scoop, pour, and burn your way to mastery in the HoloLAB. Your holographic host Earl and his sidekick Meyer guide you through a series of mini-labs that lead up to an ultimate lab challenge. Score achievements and do your best to earn an elemental trophy in this amazing Labstravaganza.

Virtual Lab Practice. Real Lab Mastery.

HoloLAB Champions (formerly SuperChem VR) is supported in part by the Institute of Education Sciences, U.S. Department of Education, through the Small Business Innovation Research (SBIR) program contract ED-IES-17-C-0035 to Schell Games. The opinions expressed are those of the authors and do not necessarily represent views of the Institute or the U.S. Department of Education.

# data[].attributes.attachment_link.description
"It's this sort of attention to detail that makes HoloLAB Champions a shining example of what can be achieved when mixing the worlds of VR entertainment and education together, thoroughly focusing your attention for the entire time."4 out of 5 stars - VRFocus "Although built as an educational tool, HoloLAB Champions also succeeds as a completely new way to experience practical science.

# data[].attributes.body
https://pubs.acs.org/doi/pdf/10.1021/acs.jchemed.8b00017

# data[].attributes.body
https://teachchemistry.org/classroom-resources/simulations

# data[].attributes.attachment_link.readable_text
View our unlocked repository of interactive Simulations. To view a Simulation, click the Simulation's title.

Teacher Members, you can share Simulations without generating a Student Pass.

Simulation

In this simulation, students will complete a calculation in order to determine either the molarity of solution, volume of solution, or mass of solute needed. Additionally the associated particle diagram for the solution will be displayed to help students better visualize the solution at the particulate level. Finally, students will gain familiarity with the proper lab techniques for preparing a solution as they are lead through a step-by-step animated process demonstrating this procedure.

Simulation

In this simulation, students will reference an activity series and a solubility chart to accurately predict the products of single replacement and double replacement chemical reactions. Associated particle diagrams will be displayed to help students better comprehend the reaction at the particulate level. Students will also be asked to balance the chemical equation. The simulation is designed as a five question quiz for students to use multiple times.

Simulation

In the May 2018 simulation, students investigate several factors that can affect the initial rate of a chemical reaction, including concentration, temperature, surface area of the reactants, and addition of a catalyst.

Simulation

In this simulation, students practice classifying different chemical reactions, balancing equations, and solving stoichiometry problems.

Simulation

In the May 2017 simulation, students first learn how the average atomic mass is determined through a tutorial based on the isotope abundance for Carbon. Students will then interact within a workspace where they will select the number of isotopes, the mass of each isotope as well as their abundancies in order to successfully build a mystery element. Finally they will use their choices to calculate the average atomic mass of the mystery element.

# data[].attributes.attachment_link.title
Classroom Resources | Simulations | AACT

# data[].attributes.attachment_link.description
AACT is a professional community by and for K-12 teachers of chemistry

# data[].attributes.attachment_link.title
Labster | 150+ virtual labs for universities and high schools

# data[].attributes.attachment_link.description
Bring science class online with Labster's catalog of 150+ virtual lab simulations. We cover biology, chemistry, and other sciences. Get a free demo today!

# data[].attributes.body
https://gizmos.explorelearning.com/index.cfm?method=cUserSecure.dspTeacherHome

# data[].attributes.attachment_link.provider_name
ExploreLearning : Get hands-on, minds-on in math and science

# data[].attributes.attachment_link.readable_text
Select an inquiry type above for suggestions

Please provide as much of the following information as possible:

Name of Gizmo

Detailed description of issue

Device being used

Username

Browser being used

Location: Home, or school

Please provide as much information as possible in your request.

Please provide your name and the name of your school and/or district.

Please provide as much information as possible in your request.

Please provide:

Your name

The name of you school and/or district

Contract number

# data[].attributes.attachment_link.title
ExploreLearning Gizmos: Math & Science Virtual Labs and Simulations

# data[].attributes.attachment_link.description
Select an inquiry type above for suggestions Please provide as much of the following information as possible: Name of Gizmo Detailed description of issue Device being used Username Browser being used Location: Home, or school Please provide as much information as possible in your request.

# data[].attributes.body
Charoontham, O. (2020). ผล ของ การ จัดการ เรียน การ สอน โดย ใช้ โครง งาน เป็น ฐาน ที่ มี ผล ต่อ ผล สัมฤทธิ์ ทางการ เรียน วิชา วิทยาศาสตร์ และ ความ สามารถ ใน การ แก้ ปัญหา ของ นักเรียน ชั้น มัธยมศึกษา ตอน ต้น. Journal of Research and Development Institute Rajabhat Maha Sarakham University, 7(1), 225-240.

# data[].attributes.headline
Sukontorn, B., & Chittradub, S. (2020). แนวทาง การ ใช้ ห้องเรียน กลับ ด้าน ใน การ เรียน การ สอน วิชา เคมี สำหรับ นักเรียน มัธยมศึกษา ตอน ปลาย ที่ มี ผล สัมฤทธิ์ ทางการ เรียน ต่ำ. KKU Research Journal (Graduate Studies) Humanities and Social Sciences, 8(1), 13-25.

# data[].attributes.subject
Sukontorn, B., & Chittradub, S. (2020). แนวทาง การ ใช้ ห้องเรียน กลับ ด้าน ใน การ เรียน การ สอน วิชา เคมี สำหรับ นักเรียน มัธยมศึกษา ตอน ปลาย ที่ มี ผล สัมฤทธิ์ ทางการ เรียน ต่ำ. KKU Research Journal (Graduate Studies) Humanities and Social Sciences, 8(1), 13-25.

# data[].attributes.headline
Agbonifo, O. C., Sarumi, O. A., & Akinola, Y. M. (2020). A chemistry laboratory platform enhanced with virtual reality for students’ adaptive learning. Research in Learning Technology, 28.

# data[].attributes.subject
Agbonifo, O. C., Sarumi, O. A., & Akinola, Y. M. (2020). A chemistry laboratory platform enhanced with virtual reality for students’ adaptive learning. Research in Learning Technology, 28.

# data[].attributes.headline
Chatwan, T., Bongkotphet, T., & Vorasingha, A. (2019). การ จัดการ เรียน รู้ โดย ใช้ แบบ จำลอง เป็น ฐาน ร่วม กับ เทคโนโลยี เสมือน จริง เพื่อ พัฒนา แบบ จำลอง ทาง ความ คิด เรื่อง พันธะ โค วา เลน ต์. Humanities and Social Sciences Journal of Pibulsongkram Rajabhat University, 13(1), 266-281.

# data[].attributes.subject
Chatwan, T., Bongkotphet, T., & Vorasingha, A. (2019). การ จัดการ เรียน รู้ โดย ใช้ แบบ จำลอง เป็น ฐาน ร่วม กับ เทคโนโลยี เสมือน จริง เพื่อ พัฒนา แบบ จำลอง ทาง ความ คิด เรื่อง พันธะ โค วา เลน ต์. Humanities and Social Sciences Journal of Pibulsongkram Rajabhat University, 13(1), 266-281.

# data[].attributes.body
Popova, S. V., Petrischeva, L. P., Popova, E. E., & Ushakova, O. V. (2020, November). Modern educational formats: technology of flipped chemistry teaching. In Journal of Physics: Conference Series (Vol. 1691, No. 1, p. 012193). IOP Publishing.

# data[].attributes.headline
พวง ระย้า, ก ฤ ษ ณะ, นุ กูล ธรรม, กุลธิดา, วรรณ เกตุ ศิริ, & ทัศ ต ริน. (2021). การ พัฒนา ทักษะ การ แก้ ปัญหา ของ นักศึกษา ครู เคมี ด้วย กิจกรรม สะ เต็ม ศึกษา แบบ สืบเสาะ หาความ รู้ บูร ณา การ กระบวนการ ออกแบบ เชิง วิศวกรรม. วารสาร หน่วย วิจัย วิทยาศาสตร์ เทคโนโลยี และ สิ่งแวดล้อม เพื่อ การ เรียน รู้, 12(2), Abstract.

# data[].attributes.subject
พวง ระย้า, ก ฤ ษ ณะ, นุ กูล ธรรม, กุลธิดา, วรรณ เกตุ ศิริ, & ทัศ ต ริน. (2021). การ พัฒนา ทักษะ การ แก้ ปัญหา ของ นักศึกษา ครู เคมี ด้วย กิจกรรม สะ เต็ม ศึกษา แบบ สืบเสาะ หาความ รู้ บูร ณา การ กระบวนการ ออกแบบ เชิง วิศวกรรม. วารสาร หน่วย วิจัย วิทยาศาสตร์ เทคโนโลยี และ สิ่งแวดล้อม เพื่อ การ เรียน รู้, 12(2), Abstract.

# data[].attributes.headline
Fung, F. M., Choo, W. Y., Ardisara, A., Zimmermann, C. D., Watts, S., Koscielniak, T., ... & Dumke, R. (2019). Applying a virtual reality platform in environmental chemistry education to conduct a field trip to an overseas site.

# data[].attributes.subject
Fung, F. M., Choo, W. Y., Ardisara, A., Zimmermann, C. D., Watts, S., Koscielniak, T., ... & Dumke, R. (2019). Applying a virtual reality platform in environmental chemistry education to conduct a field trip to an overseas site.

# data[].attributes.headline
Khanthong, N., Tiamkaew, E., & Khruahong, S. (2020). การ พัฒนา แอ ป พลิ เค ชัน เทคโนโลยี ความ จริง เสมือน สำหรับ การ เรียน รู้ เรื่อง อะตอม และ การ รวม อะตอม ของ ธาตุ เคมี เป็น สารประกอบ. Journal of Applied Informatics and Technology, 2(2).

# data[].attributes.subject
Khanthong, N., Tiamkaew, E., & Khruahong, S. (2020). การ พัฒนา แอ ป พลิ เค ชัน เทคโนโลยี ความ จริง เสมือน สำหรับ การ เรียน รู้ เรื่อง อะตอม และ การ รวม อะตอม ของ ธาตุ เคมี เป็น สารประกอบ. Journal of Applied Informatics and Technology, 2(2).

# data[].attributes.headline
Khine, M. S. (2019). Steam education. Springer Berlin Heidelberg,.

# data[].attributes.subject
Khine, M. S. (2019). Steam education. Springer Berlin Heidelberg,.

# data[].attributes.headline
Jonathan Sing Huat Ong, Prasanth Rajan Mohan, Jia Yi Han, Jia Ying Chew, and Fun Man FungJournal of Chemical Education 2021 98 (8), 2699-2703DOI: 10.1021/acs.jchemed.1c00201

# data[].attributes.subject
Jonathan Sing Huat Ong, Prasanth Rajan Mohan, Jia Yi Han, Jia Ying Chew, and Fun Man FungJournal of Chemical Education 2021 98 (8), 2699-2703DOI: 10.1021/acs.jchemed.1c00201

# data[].attributes.headline
Sukontorn, B., & Chittradub, S. (2020). Guidelines of Using the Flipped Classroom in Chemistry Instruction for Upper-Secondary Students with Low Achievement. KKU Research Journal (Graduate Studies) Humanities and Social Sciences, 8(1), 13-25.

# data[].attributes.subject
Sukontorn, B., & Chittradub, S. (2020). Guidelines of Using the Flipped Classroom in Chemistry Instruction for Upper-Secondary Students with Low Achievement. KKU Research Journal (Graduate Studies) Humanities and Social Sciences, 8(1), 13-25.

# data[].attributes.headline
Khanthong, N., Tiamkaew, E., & Khruahong, S. (2020). The Development of Augmented Reality Technology Applications for Learning about Elements and Chemical Compounds. Journal of Applied Informatics and Technology, 2(2), 77-87. 

# data[].attributes.subject
Khanthong, N., Tiamkaew, E., & Khruahong, S. (2020). The Development of Augmented Reality Technology Applications for Learning about Elements and Chemical Compounds. Journal of Applied Informatics and Technology, 2(2), 77-87. 

# data[].attributes.headline
นิ น นา ท์ จันทร์ สู

# data[].attributes.body
นิ น นา ท์ จันทร์ สูรย์, & นว ศิษฏ์ รักษ์ บํา รุ ง. (2018). ความ รู้ เนื้อหา ผสาน วิธี สอน และ เทคโนโลยี ใน ห้องเรียน เคมี โดย ใช้ สถานการณ์ จำลอง แบบ มี ปฏิสัมพันธ์ ของ PhET. วารสาร วิทยาศาสตร์ และ วิทยาศาสตร์ ศึกษา (JSSE), 1(1), 109-121.

# data[].attributes.headline
 สุดา รัตน์ สัน จร รัตน์, & ดุจ เดือน ไชย พิชิต. (2021). การ พัฒนา ความ สามารถ ใน การ คิด อย่าง มี วิจารณญาณ และ ความ สามารถ ใน การ แก้ ปัญหา โดย ใช้ การ จัดการ เรียน รู้ ปัญหา เป็น ฐาน (PBL) ร่วม กับ ผัง กราฟิก ของ นักเรียน ชั้น มัธยมศึกษา ปี ที่ 5. Journal of Roi Kaensarn Academi, 6(7), 160-175.

# data[].attributes.subject
 สุดา รัตน์ สัน จร รัตน์, & ดุจ เดือน ไชย พิชิต. (2021). การ พัฒนา ความ สามารถ ใน การ คิด อย่าง มี วิจารณญาณ และ ความ สามารถ ใน การ แก้ ปัญหา โดย ใช้ การ จัดการ เรียน รู้ ปัญหา เป็น ฐาน (PBL) ร่วม กับ ผัง กราฟิก ของ นักเรียน ชั้น มัธยมศึกษา ปี ที่ 5. Journal of Roi Kaensarn Academi, 6(7), 160-175.

# data[].attributes.headline
Nersesian, E., Spryszynski, A., & Lee, M. J. (2019, March). Integration of virtual reality in secondary STEM education. In 2019 IEEE Integrated STEM Education Conference (ISEC) (pp. 83-90). IEEE.

# data[].attributes.subject
Nersesian, E., Spryszynski, A., & Lee, M. J. (2019, March). Integration of virtual reality in secondary STEM education. In 2019 IEEE Integrated STEM Education Conference (ISEC) (pp. 83-90). IEEE.

# data[].attributes.headline
อจบ.York, S., Lavi, R., Dori, Y. J., & Orgill, M. (2019). Applications of systems thinking in STEM education. Journal of Chemical Education, 96(12), 2742-2751.

# data[].attributes.subject
อจบ.York, S., Lavi, R., Dori, Y. J., & Orgill, M. (2019). Applications of systems thinking in STEM education. Journal of Chemical Education, 96(12), 2742-2751.

# data[].attributes.body
York, S., Lavi, R., Dori, Y. J., & Orgill, M. (2019). Applications of systems thinking in STEM education. Journal of Chemical Education, 96(12), 2742-2751.

# data[].attributes.body
ชนิสรา 151
พราวฝัน 160

# data[].attributes.body
ชนิสรา 151
พราวฝัน 160

# data[].attributes.body
https://www.canva.com/design/DAEwXu9q9Ms/66UBz1lk0EHpngcWhsO-dQ/view?utm_content=DAEwXu9q9Ms&utm_campaign=designshare&utm_medium=link&utm_source=publishsharelink

# data[].attributes.body
ธนสร 155
นพจิรา 156

# data[].attributes.headline
วิทย์ฯกายภาพ 2.1

# data[].attributes.subject
วิทย์ฯกายภาพ 2.1

# data[].attributes.body
เบญญาภา 157
ปพัชญา 159

# data[].attributes.attachment_link.title
วิทย์กายภาพ 2.1