Technology-Supported Inquiry in STEM Teacher Education:

This chapter explores how modern collaborative educational technologies can be implemented in STEM teacher education in order to support teacher-candidates in (1) acquiring inquiry-based teaching skills, (2) forming positive attitudes about inquiry-based STEM education, and (3) building resiliency in the face of initial failure of inquiry-based pedagogies (Milner-Bolotin, 2016b). The last two points are especially important, as there is ample research evidence that when instructors lack adequate support, they are likely to give up on implementing innovative research-based pedagogies in the face of early adoption failure (Lasry, Guillemette, & Mazur, 2014; Mazur, 1997a; Wieman & Perkins, 2005). Thus, inadequate support for K-12 and post-secondary STEM educators for reforming their teaching coupled with the limited opportunities for teacher collaboration result in an ever growing gap between research-informed and classroom-enacted educational practices (Cole & Knowles, 2000; Milner-Bolotin, 2014a). This explains why increased access to educational technologies does not necessarily guarantee a wider adoption of inquiry-based pedagogies and improved learning. In order to promote inquiry-based learning and active student engagement in STEM, K-12 and post-secondary instructors have to be supported in adopting new pedagogical approaches (Harris & Hofer, 2011; Shelton, 2015). This requires reimagining STEM teacher education, pedagogical preparation of post-secondary instructors, as well as in-service professional development (Lee & Tsai, 2010; Niess, 2005). If we fail to do so, many instructors will continue to ignore the mounting research evidence about how students learn and how STEM subjects can be taught more effectively (Bransford, Brown, & Cocking, 2002). Moreover, a large number of STEM instructors will inevitably revert to much safer but also less effective teacher-centered pedagogies they had experienced as students (Shelton, 2015; Wieman, 2012; Wieman & Perkins, 2005). This is one of the key reasons why the substantial governmental investments and half-a-century long education reform efforts in North America and in Europe aimed at promoting inquiry-based education have rarely brought the desired outcomes (Feder, 2010; Krajcik & Mun, 2014; National Research Council, 2012; Pollock, 2004).

The goals of STEM education, the role of inquiry, the tools available to modern students, as well as the population of students in K-12 STEM classrooms have changed dramatically over the last few decades (Cuban, 1990; National Research Council, 2013). In the 21^st century we cannot afford to leave the majority of our population outside of STEM fields, as every student who disengages from STEM in K-12 closes multiple future opportunities for themselves inside and outside of STEM-related professions (Chachashvili-Bolotin, Milner-Bolotin, & Lissitsa, 2016; Let's Talk Science, 2013, 2015). In the current economic reality, STEM engagement should not be limited to a select few students, as it was common in North America during the post-Sputnik era, but should become an integral part of K-12 education for all (DeBoer, 1991; Let's Talk Science, 2012).

In this chapter we investigate how modern educational technologies can help to prepare the next generation of teachers who will be open to and capable of engaging their students in inquiry-based STEM learning (Jones & Leagon, 2014; Milner-Bolotin, 2016c). We focus on K-12 teacher education, as unlike their post-secondary colleagues, teachers in North America have to earn a teaching certification in order to be allowed to teach in the K-12 public school system. Teacher education is a perfect opportunity to expose future teachers to inquiry-based pedagogies and to available support networks. However, before discussing STEM teacher education that promotes technology-supported inquiry, it is important to highlight some relevant research on the topic.

Inquiry-Based STEM Education: Past, Present, and Future

A quick Google search for inquiry-based STEM education generates more than 1,210,000 results. There is little doubt that inquiry-based education has drawn ample attention from governments, educational administrators, and the community at large. Most of the documents produced by educational bodies in Canada, the United States, Europe and worldwide in the last decades emphasize inquiry, especially when it applies to STEM education (British Columbia Ministry of Education, 2015; BSCS, 2008; Crawford, 2007; Feder, 2010; R. R. Hake, 2007; National Research Council, 2013). Indeed, the term is often used broadly and indiscriminately. However, by labeling a “hands-on” classroom activity as inquiry-based, we cannot solve the problem of student growing disengagement from STEM fields and their declining performance on international assessments (Let's Talk Science, 2013; OECD, 2014). Inquiry-based STEM education is a complex, contextual and multi-faceted phenomenon that requires skillful facilitation and extensive subject and pedagogical knowledge from the teacher. Without contextualizing inquiry-based STEM learning, defining what it is and what it is not, we limit our ability (a) to evaluate if the teaching approaches implemented under the inquiry-based STEM education umbrella are indeed inquiry-based; (b) to understand how to support teachers in facilitating inquiry-based learning; and (c) to provide constructive feedback to teachers on the pedagogical effectiveness of these approaches and ways of enhancing them (Abd-El-Khalick et al., 2004; Eugenia Etkina et al., 2010).

The idea of learning by inquiry goes back thousands of years to the teachings of ancient Greeks. Socrates, Plato and Euclid used questioning and logic as a way to get to “true knowledge”. Etymologically, the modern English verb inquire has its roots in the French enquerre and in the Medieval Latin inquerere, meaning to see into something, to find something out by asking and seeking information. However, inquiry as a pedagogical approach was not common in American schools until the early 20^th century. John Dewey (1859-1953), an American philosopher, psychologist and educational reformer, brought inquiry-based learning and its role in a child’s development into the spotlight (Dewey, 1938). Under the influence of the last wave of educational reforms in North America, 21^st century scholars and educators keep redefining the spectrum of learning environments under the umbrella of inquiry-based STEM education (An, 2015; Eugenia Etkina et al., 2010; Eugenia Etkina, Planinši, & Vollmer, 2013; E. Etkina, Van Heuvelen, Brookes, & Mills, 2002; Hmelo-Silver, Duncan, & Chinn, 2012; Milner-Bolotin, 2012; National Research Council, 2012; Tan & Caleon, 2016). Still, they haven’t yet reached an agreement regarding what inquiry-based STEM education is, and most importantly, what it is not. As Tan and Caleon (2016) write:

The current vision of science education in myriad educational contexts encourages students to learn through the process of science inquiry. Science inquiry has been used to promote conceptual learning and engage learners in an active process of meaning-making and investigation to understand the world around them. The science inquiry process typically involves asking questions and defining problems; constructing explanations and designing solutions; planning and carrying out investigations; analyzing and interpreting data; and engaging in argument from evidence. Despite the importance and provision of new directions and standards about science inquiry, ambiguities in conceptualizations of inquiry still exist. These conceptualizations may serve as barriers to students learning science. (p. 168)

While being fully aware of the challenges described above, in this chapter we start with the vision of inquiry-based STEM education found in the National Science Standards (National Research Council, 2012; Olson & Loucks-Horsley, 2000). Next we expand it, through emphasizing conceptual understanding and meaning making in STEM learning (Minner, Levy, & Century, 2010). Consequently, in this chapter, inquiry-based STEM learning is described as an environment where the learner:

1. Engages in answering meaningful STEM-oriented questions
2. Relies on gathered research evidence to answer these questions
3. Formulates testable conceptually-oriented explanations based on this evidence
4. Designs and conducts experiments (multiple iterations) to test these explanations
5. Makes sense of the results, connects them to prior knowledge, and refines the findings
6. Communicates and justifies research findings, and poses new questions.

This list highlights why creating inquiry-based STEM learning environments is so challenging. It is fraught with ambiguities both for the students and for the teachers designing these learning environments and evaluating student learning outcomes (Jonassen & Land, 2012). The more open these environments are, the more likely the teachers themselves might not know all the answers and will be required to engage in an authentic inquiry together with their students. This will require teachers to possess broad STEM knowledge, necessary inquiry skills, and confidence in their ability to figure things out as opposed to teaching from the textbook. Akin to scientific inquiry happening in research labs, inquiry-based learning relies on ongoing feedback, refinement and adjustment, which can be achieved through student collaboration, as well as continuous interactions between a student and a teacher. Therefore, inquiry-based teaching is a reflective and an iterative endeavour.

Pedagogically effective inquiry-based learning environments are still uncommon in K-12 classrooms. Thus, it is unlikely that current STEM teacher-candidates had much experience with them as K-12 students, and even less likely that they were encouraged to reflect on these environments as future teachers. Therefore, it is crucial that they experience inquiry in their STEM methods courses as learners and reflect on this process as future teachers before implementing inquiry-based lessons during the practicum and after graduation (Milner-Bolotin, Fisher, & MacDonald, 2013). In the next section, we delineate the conceptual theoretical framework incorporated in this chapter.

Theoretical Framework for Studying STEM Teacher Education

During the last half a century, education researchers have suggested multiple conceptual frameworks for investigating the development of teacher knowledge (Abbitt, 2011; Ball, Thames, & Phelps, 2008; Blömeke & Delaney, 2012; Corrigan, Gunstone, & Dillon, 2011; Hourigan & Donaghue, 2013; Koh & Divaharan, 2011). These frameworks can be used to study how future STEM teachers learn to teach by inquiry and acquire positive attitudes about inquiry-based STEM education. The original Pedagogical Content Knowledge (PCK) framework proposed by Shulman more than three decades ago (Shulman, 1986a, 1986b) will serve the backbone of the current study. Shulman emphasized that teachers should possess subject-specific content knowledge (CK), general pedagogical knowledge (PK), and pedagogical content knowledge (PCK), where PCK can be considered to be the overlap of the two. The PCK framework was later expanded to include the knowledge of educational technologies—technological knowledge (TK)—thus morphing into the Technological Pedagogical (and) Content Knowledge framework (TPACK) (Mishra & Koehler, 2006). The latter framework separates the content specific knowledge usually acquired by teacher-candidates during their B.Sc. degree (i.e., the knowledge of specific STEM disciplines, such as mathematics, physics or chemistry) from the knowledge of how these subjects can be taught in the K–12 context, and how technology can be used to enhance student learning (Figure 1).

Figure 1. Technological Pedagogical and Content Knowledge (TPACK) framework by Koehler and Mishra (2015)

In their conceptual framework for mathematics teacher competencies, Blömeke and Delaney (2012) referred to the TPACK aspect of teacher knowledge as cognitive abilities or professional knowledge. We will extend their theoretical framework to describe STEM teacher competencies (Figure 2). We will use TPACK in a greater sense, including not only the overlap of the three knowledge domains (CK, PK, and TK), but also each one of them. They also emphasized affective–motivational characteristics, such as professional beliefs, motivation, and self-regulation. This is relevant to all STEM fields, as teachers’ attitudes and predispositions towards inquiry-based STEM learning are crucial for the successful implementation of these pedagogies.

Figure 2. A big picture of STEM teacher competences, as a combination of cognitive abilities, affective characteristics and potential opportunities for TPACK growth as a result of collaboration with peers (Teacher Zone of Proximal Development or T-ZPD). Arrows indicate the interactions between different facets of teachers’ professional competencies.

This chapter builds on the original framework by Blömeke and Delaney (2012) by emphasizing that teachers’ competencies, similarly to student knowledge, can be developed through collaboration with peers (Figure 2). Instead of looking at teachers’ competencies as static, we consider their dynamic nature, asking: How can these competencies be developed if teachers are encouraged to collaborate with peers and more experienced teachers? Therefore, the theoretical framework adopted in this chapter focuses on the potential growth of STEM teachers’ competencies as a result of this collaboration. This approach is an adaptation of the original Zone of Proximal Development concept suggested by Vygotsky, to the context of teaching and teacher-education (Vygotsky, 1978). We refer to it as the Teacher Zone of Proximal Development (T-ZPD). T-ZPD describes the gap between what a teacher has already mastered (the actual level of development, as expressed by their current TPACK) and what they can achieve when provided with opportunities to collaborate with peers and more experienced educators. T-ZPD represents the potential for the development of teachers’ TPACK (Figure 3). The need to consider the dynamic nature of TPACK affected by teachers’ interactions with peers, students, parents, administrators, and the society at large, reflects our belief in teaching as a highly professional endeavour. In order to keep up-to-date, teachers must always learn, update and question their knowledge, interact with others in the field, and continuously reflect on their practice. The view of ever-evolving mastery of teaching and the importance of a community in becoming and being an effective teacher is situated in Vygotsky’s socio-cultural learning theory (Daniels, 2001; Vygotsky, 1978).

Figure 3. Growth of teachers’ TPACK due to collaboration with peers more experienced teachers. The light blue area in the left image shows the Teacher-Zone of Proximal Development (T-ZPD). As a result of collaboration all aspects of teachers’ knowledge have grown, including their TPACK.

It is difficult to acquire inquiry-based teaching skills while working in isolation. It is more effective to master these skills in the process of apprenticeship and collaboration with peers. However, this collaboration should not be an isolated occurrence. This often happens when teachers attend one-time professional development events that are rarely followed up by long-term collaboration with peers focussed on the implementation of these pedagogies. These one-time professional development opportunities rarely bring sustained changes in teachers’ practice (Luft & Hewson, 2014). In order to support teachers in moving towards inquiry-based STEM teaching, they have to have multiple opportunities to inquire about their own practice, adopt and adapt new pedagogies, collaborate with colleagues, and acquire the necessary TPACK(Burridge & Carpenter, 2013; Krajcik & Mun, 2014) (British Columbia Ministry of Education, 2015; Schmidt et al., 2011).

The following section describes five different collaborative technology-enhanced pedagogies that can be used in STEM teacher education in order to help teacher-candidates (1) acquire relevant inquiry-based teaching skills, (2) form positive attitudes about inquiry-based STEM education, and (3) build resiliency in the face of initial failure of inquiry-based teaching practices in their future classrooms (Milner-Bolotin, 2016b). All these pedagogies were used simultaneously in the STEM methods courses in order to provide teacher-candidates with ample opportunities for collaborative development of their teaching competencies and positive attitudes about inquiry-based STEM education, as well as the resiliency and the capacity needed to overcome initial obstacles in implementing inquiry in their own classrooms.

This section considers five different collaborative technology-enhanced pedagogies simultaneously implemented in STEM teacher education courses in order to prepare teacher-candidates for enacting inquiry-based teaching. These technologies include: Electronic response systems (implemented with Peer Instruction), PeerWise collaborative database, data acquisition tools, computer simulations and modeling software, and Collaborative Learning Annotation System (CLAS) (Milner-Bolotin, 2014b, 2016c) (Table 1). While there are many potential educational technologies relevant to teacher education, the choice of the five technologies mentioned above is deliberate. These technologies are all low cost or free; they are relevant to both K-12 and post-secondary classrooms; they promote collaboration and reflection; they help teacher-candidates acquire relevant TPACK (Koehler & Mishra, 2015); they help teacher-candidates develop positive attitudes about research-informed inquiry-based education; and lastly, they support teacher-candidates in cultivating resilience in the face of initial failure and the courage to persevere at inquiry-based teaching. As Winston Churchill once said “Success is not final, failure is not fatal: it is the courage to continue that counts”. This is the key message we would like to convey to future teachers: teaching is a life-long process of learning and personal growth, filled both with failures and successes. The second message is that reflection and peer collaboration are valuable tools for supporting teachers when they work on modifying their pedagogy and improving their practice.

These technologies were implemented in our STEM methods courses during a year-long secondary STEM Teacher Education Program (http://teach.educ.ubc.ca/). About 20 teacher-candidates took part in these 13-week 3 credit courses (Milner-Bolotin, Egersdorfer, & Vinayagam, 2016). The next sections outline how these courses supported the development of teacher-candidates’ TPACK, positive attitudes about inquiry-based education, and confidence in facilitating inquiry-based learning in the future.

Table 1. Description and pedagogical goals of five different technology-enhanced learning environments used in STEM teacher education aimed at promoting inquiry-based teaching and learning

	Pedagogical Description/technology	Pedagogical Goals and How They Are Promoted
1. Peer Instruction	Pedagogical description: Technology is used to collect continuous student feedback and adjust teaching to address student conceptual difficulties via using multiple-choice conceptual questions. Peer Instruction relies on teacher’s abilities to ask conceptual questions, identify student difficulties and support student inquiry as opposed to providing them with the answers. Despite the availability of technology and possibilities of using low-tech versions in small classes, Peer Instruction is not as widely used in K-12 as in post-secondary STEM classrooms. Technology: Electronic response systems, smart phones, personal computers, iPads, or a low tech version of QR cards used for individual student voting wherein a teacher uses a phone to collect data.	The goals – to support teacher-candidates in: • Developing their PCK • Reflecting on their STEM PCK and on the difference between learning by memorization and by understanding/questioning • Learning to identify student conceptual difficulties and to ask different levels of questions that promote inquiry and help build conceptual understanding (Bloom, 1956) How these goals are promoted: • By modeling effective conceptual questions during methods courses and inviting teacher-candidates to experience Peer Instruction as learners and teachers • By emphasizing the value of peer collaboration • By experiencing formative assessment and peer collaboration in practice as learners and reflecting on it as future teachers.
2. Peer Wise-based pedagogy	Pedagogical description: PeerWise database supports a community of learners who collaborate on designing multiple-choice questions. PeerWise and Peer Instruction both emphasize formative assessment using conceptual multiple-choice questions and peer collaboration. Technology: An online social platform for sharing, responding to, reflecting on, editing, and improving multiple-choice questions. It allows students to contribute their multiple-choice questions, respond to the questions asked by their peers, rate the quality of questions and explanations, and suggest improvements.	The goals – to support teacher-candidates in: • All of the above under Peer Instruction, plus • Designing meaningful conceptual STEM questions that open opportunities for inquiry • Learning to identify student conceptual difficulties and to ask different levels of questions that promote inquiry and help build conceptual understanding (Bloom, 1956) • Learning to give and receive constructive feedback. How these goals are promoted: • By designing, responding to and providing constructive feedback to conceptual questions • By thinking of meaningful distractors (wrong answers for multiple-questions) • By discussing these questions with peers • By learning to receive constructive feedback and to act on suggestions • By realizing that they still have a lot to learn.
3. Real life data as an impetus for inquiry	Pedagogical description: Technology enables learners to explore “what-if” questions about the real world via collecting and analysing real-time data, conducting experiments and answering questions experimentally that could not have been answered before. The collected data can include temperature, pressure, position of objects, PH levels of different solutions, etc. This pedagogy invites students to ask and answer their own inquiry questions, thus engaging them in authentic STEM learning. Technology: Examples include Logger Pro sensors (Milner-Bolotin & Moll, 2008), various smart phone applications, etc.	The goals – to support teacher-candidates in: • Designing and facilitating inquiry-based STEM lessons both during their class discussions and in labs • Design inquiry-based labs • Learning to guide students in asking questions • Learning to explain real-life data and use it to test STEM hypotheses How these goals are promoted: • By helping teacher-candidates to experience data-driven inquiry • By making them comfortable with the use of various technologies for real-life data collection • By modeling investigations based on live data collection and analysis • By modeling the use of technology to bridge STEM to everyday life
4. Pedagogy that utilizes computer simulations & modeling	Pedagogical description: Various computer simulations and modeling tools are used to ask “what-if” questions about the real world or about more abstract phenomena. This pedagogy invites students to think more abstractly, while using authentic research tools. Learners can use these tools to ask and answer their own inquiry questions, thus engaging them in authentic STEM learning. Technology: Computer simulations such as PhET, data modeling and analysis tools, such as GeoGebra, programming tools, etc.	The goals – to support teacher-candidates in: • Inquiring about abstract (or not so abstract) phenomena through manipulating different parameters of the system (modeling, simulations) • Experiencing scientific inquiry first hand by asking and answering “what-if” questions • Acquiring STEM intuition, by learning to connect various representations of phenomena with the implications of these representations (e.g., the meaning of formulae), such as mathematical descriptions with scientific outcomes. • Linking theory to practice (virtual versus real labs) How these goals are promoted: • By helping teacher-candidates to experience data-driven inquiry and ways of scientific inquiry
5. Collaborative Learning Annotation System (CLAS)	Pedagogical description: This pedagogy emphasizes continuous reflection. Teacher-candidates are invited not only to practice their teaching in a supportive environment, but also to reflect on it and improve it as a result. Technology: CLAS is a media player that allows recording, sharing, and commenting on videos. Videos uploaded to CLAS are stored on a secure server at UBC and allow control over who has access to them. CLAS is also mobile compatible, allowing students to record videos and make comments directly from their mobile devices.	The goals – to support teacher-candidates in: • Becoming a reflective practitioner • Becoming a teacher who is open to peer collaboration via learning from others and supporting them • Becoming a confident and open-minded teacher who is open to suggestions in order to improve their practice. How these goals are promoted: • By learning to reflect on their teaching, provide constructive feedback, accept feedback and act on it • By practicing their teaching in a friendly environment • By collaborating with peers in a safe environment • By comparing multiple iterations of different lessons and reflecting on their pedagogical progress • By building self-confidence in their teaching abilities.

Peer Instruction: Learning STEM by Questioning and Collaborating

Peer Instruction pedagogy was originally proposed by a Harvard Physics Professor – Eric Mazur almost 30 years ago (Mazur, 1997b, 1997c). Peer Instruction is a form of live formative assessment that is continuously used by an instructor to support student learning and tailor instruction to students’ needs. In the last decades Peer Instruction has become a very common and widely researched interactive engagement pedagogy in post-secondary STEM education (Fraser et al., 2014; Richard R. Hake, 1998; Lasry, Guillemette, Dugdale, et al., 2014; Wieman, 2012). Peer Instruction uses flashcards, electronic response systems (clickers), or mobile devices (virtual clickers) to engage students in meaningful learning by asking them carefully crafted conceptual multiple-choice questions that target common student difficulties and misconceptions (Lasry, 2008; Lasry, Mazur, & Watkins, 2008). The students are given a chance to think about these questions and provide individual responses. When Peer Instruction is used with clickers, the histogram of student responses is shared with the entire class. Then the students are invited to discuss their answers with their peers. This small group collaborative exercise is followed up by an all-class discussion led by the instructor (Milner-Bolotin, 2015a). With the proliferation of new technologies and free or low-cost versions of virtual clickers, such as plickers (Amy, 2016), Peer Instruction is becoming more and more popular in the K-12 educational system. We have written extensively about the use of Peer Instruction in STEM teacher education and will refer the readers to these papers (Lasry, 2008; Lasry, Watkins, Mazur, & Ibrahim, 2013; Milner-Bolotin, 2016b). Here we focus on how Peer Instruction implemented in STEM teacher education courses can support future teachers in promoting inquiry-based pedagogies in their own practice.

Peer Instruction relies on conceptual questions that ask learners to analyze phenomena without relying on formulae and plug-and-chug calculations (Beatty, Gerace, Leonard, & Dufresne, 2006). Figure 4 shows an example of such a question in the context of physics. The question challenges students to analyze the implications of Newton’s second law in the case of a weight-pulley system. This conceptual question can inspire a student-led independent inquiry where such a system is set up and its acceleration is investigated using Logger Pro live data collection system (Milner-Bolotin, Kotlicki, & Rieger, 2007).

Figure 4. An example of a conceptual multiple-choice physics question challenging students to analyze the implications of Newton’s second law. This question was retrieved from Mathematics and Science Teaching and Learning through Technology online database (Milner-Bolotin, 2016a).

In order to design pedagogically effective conceptual questions that can be used in Peer Instruction, teachers have to recognize potential student difficulties and common misconceptions, and offer effective ways of helping students to inquire about the phenomenon. When teacher-candidates experience Peer Instruction as learners, they realize the power of this pedagogical approach for STEM education. They also become aware of the value of STEM education research for their own practice. This is one of the reasons why noted physics educator Lillian McDermott and her colleagues called on improving physics teacher preparation through incorporating educational research into teacher education practice (McDermott, Heron, Shaffer, & Stetzer, 2006).

Peer Instruction is especially appropriate to STEM teacher education. Through the use of well-crafted conceptual questions teacher-candidates have an opportunity to realize that STEM mastery requires higher order thinking skills and an ability to think creatively and conceptually. As one teacher-candidate expressed it: “Peer Instruction gets you away from thinking physics is a math class. It gets you to really understand the science.” After earning a Bachelor degree in the relevant subject, many teacher-candidates assume that they have mastered the content knowledge they will be teaching and they have little to learn. Yet, often this mastery is rather superficial: teacher-candidates often encounter the same conceptual difficulties as secondary students (Milner-Bolotin et al., 2013). Teacher-candidates often might know the answer to a question, but they do not know why the answer holds. They might have learned some facts and relationships, but they might not have had an opportunity to inquire why these relationships hold true, which is the key element in inquiry-based teaching and learning. Inquiry is driven by curiosity and doubt, which means STEM teachers should learn not to take things for granted, but keep asking questions. Lastly, while experiencing Peer Instruction as learners, future teachers learn to listen to others, to ask questions, to articulate their thinking, and understand where somebody else might have difficulty. Implementing Peer Instruction in teacher education courses is a powerful opportunity for reflection and for deepening teacher-candidates’ TPACK, as well as helping them gain confidence in explaining complex phenomena conceptually without always relying on formulae and factual knowledge.

To support teacher-candidates in developing necessary questioning skills and enhancing their TPACK, we incorporated PeerWise, an online collaborative multiple-choice questions’ database (Denny, 2016).

PeerWise: Learning to Ask STEM Questions Through Collaboration With Peers

PeerWise is a free online collaborative tool. It supports learners in designing and sharing their multiple-choice questions, commenting and responding to peers’ questions, and eventually creating a shared resource of conceptual questions, explanations, solutions and suggestions (Milner-Bolotin, 2014b).

In our STEM methods courses teacher-candidates used PeerWise weekly as part of the PeerWise cycle sequence (Table 2). Teacher-candidates were asked on a regular basis to contribute their conceptual questions on PeerWise, answer some of the questions provided by their peers, comment on these questions, as well as respond to the comments provided to them. Thus, each PeerWise question underwent multiple iterations before its final version was generated and saved in the database.

Table 2. A PeerWise sequence outlining teacher-candidates’ expected participation

Cycle	Week	Expected Tasks
1	1	Author at least six questions and upload them to PeerWise
1	2	Answer at least 10 questions designed by your peers Provide comments on at least five of the questions you answered
2	3	Review all relevant comments on your own questions and respond when applicable Modify at least three of your questions to address the comments Author at least three additional questions
2	4	Answer at least 10 questions designed by your peers Provide comments on at least five questions you answered
Cycle 2 repeats every two weeks for the duration of the course

PeerWise is especially suitable for modeling question-driven pedagogy in STEM teacher education. It can supplement Peer Instruction, highlight the difference between plug-and-chug and conceptual questions, and show how conceptual questions enhance student understanding. Another teacher-candidate said:

I think for myself…getting away from the number-crunching questions to conceptual questions, and understanding that even though number-crunching can feel harder, it doesn’t really show how well you know something compared to conceptually, and for me PeerWise really helped me realise that.

Moreover, PeerWise requires teacher-candidates to provide constructive feedback and react in a positive and productive way to the feedback provided by peers. It increases teacher-candidates’ ability to evaluate their peers’ questions and explanations, which is crucial for improving their confidence in designing inquiry-based learning environments (Milner-Bolotin et al., 2016). As educators often adopt and adapt already existing activities to suit their pedagogical goals, an ability to become a “critical consumer” of already existing resources is a valuable skill for novice teachers.

PeerWise collaboration also emphasizes the iterative nature of designing pedagogically effective educational materials. The teachers who realize that teaching in general, and inquiry-based teaching in particular, is an iterative process and it takes time and patience to learn how to teach by inquiry and how to ask questions that can facilitate inquiry, are going to be more resilient in the face of failure. These teachers will be less likely to give up if an inquiry-based activity they have designed does not generate desired results. Another way of helping teacher-candidates to acquire inquiry-based teaching skills is to engage them in activities that utilize real-time data collection and analysis tools.

Data-Driven Inquiry in STEM Teacher Education

In order to support teacher-candidates in acquiring inquiry-based teaching skills as well as positive attitudes about inquiry, it is important to provide them with multiple opportunities to experience authentic technology-enhanced learning environments as students first and then reflect on them as future teachers (Milner-Bolotin et al., 2013; Milner-Bolotin & Moll, 2008). Data collection and analysis technology, such as the Logger Pro data acquisition system, is a great asset for supporting authentic inquiry, reducing the cost of risk-taking and allowing learners to experiment with abstract STEM ideas by connecting them to everyday life (Eijck & Roth, 2009; Milner-Bolotin, 2012; Vernier-Technology, 2016).

For example, producing and interpreting graphs and building bridges between algebraic, graphical and physical representations are often difficult for the students. This is a great opportunity for authentic inquiry activities, where students can pose questions and devise authentic experiments that will help them answer these questions (Eshach, 2014; Ruthven, Deaney, & Hennessy, 2009; Wright, 2005). In order to help students connect physical scenarios with their mathematical and physical representations, STEM teachers can use data collection and analysis tools, also referred to as sensors. For instance, Logger Pro motion detector allows students to represent the 1-D motion of a moving object as an x(t) graph (Vernier-Technology, 2016). Figure 5 shows a graph of motion produced by a student moving along a straight line in front of a motion detector. Since the data are collected and displayed in real time, the students can collaborate with peers on pursuing their own “What-if” inquiry questions. Moreover, the technology reduces the cost of failure as the experiments can be easily adjusted, improved and repeated. Similar to Peer Instruction, live data collection and analysis tools provide instantaneous formative assessment that was unimaginable before (Schuster, Undreiu, Adams, Brookes, & Milner-Bolotin, 2009). This process encourages authentic inquiry, collaboration and powerful reasoning.

Figure 5. An example an inquiry-based activity where students explore 1-D motion: a student was asked to walk in front of the motion detector in order to match a given (blue) graph with the red one (produced by the walking student)

Engaging STEM teacher-candidates in collaborative data-driven inquiry invites them to think differently about STEM education and the relationships between the inquiry that happens in the classroom and the inquiry that happens in science research labs. Conveniently, in addition to Logger Pro and similar data collection tools, many modern smartphone or tablet apps allow rather sophisticated live data collection and analysis (Maciel, 2015). Creative STEM teachers can use these 21^st century tools to promote authentic inquiry in their classrooms. However, in order for this to happen, STEM teachers have to acquire the necessary TPACK (Carr, 2012). Without it, these sophisticated tools will remain underused expensive gadgets and the goal of increased student STEM engagement will take much longer to achieve (Cuban, 2001).

Computer Simulations and Modeling: Virtual Inquiry

The data collection and analysis tools are helpful in promoting inquiry-based STEM education (Milner-Bolotin, 2016c). However, not every STEM concept can be easily demonstrated through a hands-on activity. As teacher-candidates work on designing inquiry-based lessons, they often find it challenging to help students grapple with abstract concepts. For example, the consequences of the electromagnetic induction phenomenon can be demonstrated in a lab, but in order to meaningfully understand this abstract physics concept, a more extensive inquiry is required. As a result, many novice teachers struggle with engaging students in authentic explorations of these abstract concepts in order to support student understanding.

Modern technologies such as computer simulations and dynamic modeling software offer ample opportunities to promote meaningful inquiry of abstract phenomena. We have written about this topic elsewhere (Milner-Bolotin, 2015b, 2015c, 2016b), so in this chapter these technologies will be only mentioned briefly. For example, PhET is a suite of STEM simulations built on solid educational research evidence (Wieman, Adams, Loeblein, & Perkins, 2010). They can be used to help students not only to visualize abstract ideas, but also to conduct independent research investigations in virtual environments akin to the ones conducted in real labs (Finkelstein et al., 2005).

PhET simulations open ample opportunities for developing inquiry-driven thinking, yet they are closed tools. Their designers have deliberately decided what parameters the learners will be able to manipulate. In other words, the decision about the model embedded in the simulation has been made and the learner has no input into it. Computer simulations where those decisions have been made based on educational research (such as PhET) are powerful for beginners. Yet, when the learners have acquired advanced subject knowledge and want to ask more sophisticated questions, the simulation might prove to limit their investigations.

The next level of inquiry is attained when the students create and test their own STEM models. An example of modeling technology that has the potential to support an even higher level of student creativity and empower them to experience STEM in a very personal way is dynamic modeling software, such as GeoGebra (Hohenwarter, 2014). Unlike traditional paper and pencil geometrical or algebraic constructions, where a construction or a graphical representation cannot be changed or manipulated easily, or unlike computer simulations where the underlying scientific models have been chosen by the designers, GeoGebra allows students to develop a language, propose and test their own models, dynamically test their understanding, visualize abstract relationships and eventually foster their STEM intuition (Martinovic, Karadag, & McDougall, 2014).

However, the use of these tools in STEM education does not guarantee inquiry-based learning. As mentioned above, teachers need to acquire inquiry-based teaching skills in order to be able to implement these tools effectively in their classrooms. In order to provide teacher-candidates with multiple opportunities to reflect on their inquiry-based teaching skills and improve them, we implemented the Collaborative Learning Annotation System (CLAS).

Promoting Inquiry Teaching With CLAS

CLAS is an online media player developed at the University of British Columbia (Dang, 2016). It allows uploading, sharing, and commenting on videos stored in the system, with both time-specific and general comments (Figure 6). The participants can respond to specific comments and create commenting threads. The instructor has full control of who has access to the videos. The comments made by the instructor or by the students can be private or public. Most importantly, CLAS is compatible with the videos recorded using smartphones and other common devices, such as iPads or tablets available to teacher-candidates. Thus, no additional special video-recording equipment was needed to use the system.

Figure 6. A screen shot of a CLAS interface. By clicking on different icons in the Time-specific comments area, one can read and respond to all the comments pertinent to different parts of the video. To find out more about the system visit: http://ets.educ.ubc.ca/clas/

CLAS was incorporated in the methods courses as a tool to support teacher-candidates’ reflection on inquiry-based mini-lessons they taught. Each teacher-candidate had to teach at least four different 10-15 minute long mini-lessons to their peers during the course of the term. Teacher-candidates were free to choose the topics for these mini-lessons as long as they were part of the secondary STEM curriculum and engaged learners in figuring out STEM concepts. After teacher-candidates uploaded their mini-lessons to the CLAS database, they were asked to comment on the mini-lessons of their peers and respond to the comments on their own mini-lessons. Moreover, on multiple occasions, teacher-candidates decided to incorporate the comments and to re-teach their lessons. Since all the mini-lessons were recorded, teacher-candidates were able to reflect on their own progress and think of areas for improvement.

In this process they learned to inquire about their own teaching, to provide and receive constructive feedback, and to think about how to support students in figuring out STEM concepts for themselves. The process of watching their own teaching videos for the first time was very revealing for most of the teacher-candidates. This allowed them to reflect on the gap between their own perception of learner engagement in their lessons and the real engagement as manifested in the video. This is especially important for promoting inquiry-based STEM education and student engagement, as it is very common to see how teachers’ perceptions of their own inquiry-based teaching differ drastically from the classroom realities experienced by their students.

Lastly, the positive feedback on their teaching provided by their peers and the course instructors allowed teacher-candidates to identify their strengths and gauge their own progress. As many of the teacher-candidates decided to repeat their mini-lessons, reflecting on their teaching using CLAS helped them see their teaching as a work in progress. It also helped them identify their strengths and see their improvement. Passionate and less experienced teachers are often their own worst critiques, so receiving positive and constructive support from colleagues was a much-needed boost for improving teacher-candidates’ self-confidence.

The goal of the study was to explore how using collaborative educational technologies in STEM teacher education can support teacher-candidates in moving towards inquiry-based teaching in their own classrooms. The study was motivated by our desire to provide practical recommendations for teacher educators who want to support teacher-candidates in acquiring inquiry-based skills and promote teachers’ positive attitudes towards teaching STEM by inquiry. In this study, we used five different technology-enhanced pedagogies that supported teacher-candidates’ collaboration and mutual support, while providing them with multiple opportunities for improvement (Table 1).

The main outcome of our exploration was not identifying the “perfect” technology to support teacher-candidates, but making sure that each one of the technologies used in STEM teacher education has a clear pedagogical purpose – to engage teacher-candidates in inquiry-based learning as students, encourage them to reflect on their experiences as future teachers, and eventually apply these pedagogies during their practicum and consequent teaching. We call this approach a deliberate use of technology (Milner-Bolotin, 2016b). This study has highlighted the value of purposeful implementation of technology in order to promote productive collaboration and peer support among teacher-candidates. Technology helped us to promote inquiry-based teaching during the teacher education courses and supported teacher-candidates in inquiring about their own teaching practices. This helped us to bridge the research-informed technology-enhanced STEM pedagogies to the classroom practices enacted by teacher-candidates during their practicum and post-graduation. We recommend that teacher-educators who want to promote technology-enhanced inquiry-based teaching should model the use of collaborative technologies in their own courses. Modeling research-based pedagogies in collaborative methods courses, where teacher-candidates can learn from and with each other, is important for supporting teacher-candidates’ shifts towards these pedagogical practices (Milner-Bolotin et al., 2016).

This chapter explored how modern collaborative educational technologies can be used in STEM teacher education in order to help teacher-candidates develop the necessary TPACK, positive attitudes about inquiry-based learning, and confidence in their ability to use inquiry-based pedagogies in their own classrooms. While this chapter explored the deliberate use of technology in STEM methods courses in a teacher education program, we have yet to study how teacher-candidates’ experiences during their school practicum and after graduation might influence their attitudes about inquiry-based STEM education and their ability to continue using inquiry in their own classrooms. Supporting teacher-candidates use of technology-enhanced inquiry in teacher education courses is crucial, as teacher-candidates might have limited opportunities during their school practicum to implement these research-informed pedagogies. Teacher-candidates also remain under a lot of pressure during their school practicum, as School and Faculty Advisors are the ones who decide if a teacher-candidate has passed the practicum – a key element of the teacher education program. As one of the teacher-candidates expressed it:

I wasn’t aware of the amount of pressure that would come from both the students and my School Advisor…basically in favour of plug and chug physics. I didn’t realise how much you’re going against when you try and change the way kids do physics. By the end of my practicum I didn’t do conceptual physics anymore, because the kids didn’t want it, my School Advisor didn’t want it, my Faculty Advisor didn’t want it. They wanted the kids to get through and enjoy the class more than they wanted them to struggle with the concepts…It depends on the culture of the school... I was very prepared to do conceptual physics, but when my School Advisors and Faculty Advisors told me that wasn’t what they wanted, I had no idea what physics education looked like…

Teacher-candidates can become conduits for change, but at the same time, their desire for inquiry-based teaching in a school environment where teachers want to use “plug-and-chug” pedagogy might be a dangerous strategy for them. Thus, more research is required to understand how teacher-candidates can be supported during their practicum in implementing inquiry-based pedagogies.

Lastly, even after graduation novice teachers are more vulnerable than their more experienced colleagues. Novice teachers come to a school culture that might have different attitudes about inquiry than their own. They also have to earn their reputation and address the learning objectives posed by the provincially (or state) mandated curriculum. Therefore, it is important to investigate how novice teachers can be supported in enacting inquiry-based STEM education practices their first years after graduation.

This chapter has demonstrated how five different kinds of modern collaborative educational technologies can be implemented in STEM teacher education in order to support teacher-candidates in (1) acquiring relevant inquiry-based teaching skills, (2) forming positive attitudes about inquiry-based STEM education, and (3) building resiliency in the face of initial failure of inquiry-based teaching practices. The technology-enhanced pedagogies explored here include: Peer Instruction, PeerWise, data-driven inquiry-based pedagogy, computer-supported inquiry and collaborative reflection on mini-lessons using CLAS. The use of these technologies in a supportive and collaborative learning environment has highlighted the value of collaboration with peers, reflection on their TPACK and on their teaching, and openness to changing their practice as a result of constructive feedback. Nevertheless, we have to remember that the instructors in STEM methods courses often have little influence on teacher-candidates’ experiences during their school practicum. Therefore, in order to support teacher-candidates in acquiring inquiry-based teaching skills, we have to support them during their practicum.

Lastly, this study applied a T-ZPD theoretical framework to teacher education, as much as we consider ZPD in designing learning environments for students. Based on our studies, we have found that teacher-candidates who are provided with multiple opportunities to collaborate with peers will be more likely to acquire an extensive and meaningful TPACK than their counterparts working alone (Milner-Bolotin et al., 2016). Modern technologies can provide multiple constructive opportunities for these collaborations. Thus, we challenge teacher educators to consider how technology can be implemented in STEM teacher education to inspire and support teacher-candidates in implementing inquiry-based technology-enhanced teaching practices in their own classrooms.

This research was previously published in Digital Tools and Solutions for Inquiry-Based STEM Learning edited by Ilya Levin and Dina Tsybulsky, pages 252-281, copyright year 2017 by Information Science Reference (an imprint of IGI Global).

The author would like to acknowledge Davor Egersdorfer for his thoughtful, detailed, and constructive feedback on the manuscript.

Collaborative Learning Annotation System (CLAS): An online system that enables learners to collaborate on uploaded videos.

Collaborative Teacher Inquiry: Teacher collaboration focused on inquiring about their own practices and student learning.

Computer Simulations and Real Data Collection and Analysis: Enable students to model natural phenomena either virtually or in real-life through data collection and analysis.

Inquiry-Based STEM Learning: Learning of STEM disciplines that encourages learners to ask questions, test hypotheses and ideas, and conduct experiments. It is often conducted in a collaborative environment.

Pedagogical Content Knowledge (PCK): Teacher’s knowledge expressed as an overlap of subject knowledge and pedagogical knowledge. PCK concept was introduced by Lee Shulman in 1986.

Peer Instruction: An interactive data-driven pedagogy popularized by Harvard Professor Eric Mazur in the early 1990s.

PeerWise: An online collaborative platform used for learner collaboration on multiple-choice questions.

Teacher Zone of Proximal Development (T-ZPD): The difference between the teachers’ individual TPACK and their TPACK resulting from their collaboration with peers.

Technological Pedagogical and Content Knowledge (TPACK): An expansion of the PCK that includes the relevant knowledge of subject-specific technologies. TPACK was introduced by Koehler and Mishra in the 1990s.

Chapter 42

Technology-Supported Inquiry in STEM Teacher Education: