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Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

Please note that all times are shown in the time zone of the conference. The current conference time is: 17th May 2024, 07:46:59am GMT

 
 
Session Overview
Session
10 SES 08 C JS: Preparing Preservice Teachers for Effective Mathematics Instruction: Knowledge, Affect, and Pedagogical Practices
Time:
Wednesday, 23/Aug/2023:
5:15pm - 6:45pm

Session Chair: Itxaso Tellado
Location: Rankine Building, 107 LT [Floor 1]

Capacity: 50 persons

Joint Session NW 10 & NW 24

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Presentations
10. Teacher Education Research
Paper

Exploring Preservice Teachers’ Use of Definitions for Trapezium

Ismail Zembat, Cristina Mio, Utkun Aydin, Evelyn Mclaren

University of Glasgow

Presenting Author: Zembat, Ismail; Mio, Cristina

Definitions are part of teachers’ subject matter knowledge (Delaney, 2012), and they have implications for curricular (Usiskin & Griffin, 2008) and pedagogical decisions (Zazkis & Leikin, 2008) that teachers make. Therefore, definitions play a key role in mathematics learning, teaching, and curriculum development. Teachers’ understanding of definitions gives us clues about their understanding of the concepts associated with them. Geometry is a field where definitions play a significant role and research has shown that teachers need additional support in this area (Clements & Sarama, 2011). Hence, research aiming to investigate teachers’ understanding of definitions in geometry is necessary. In this study, we focus on definitions of quadrilaterals, in particular trapeziums/trapezoids, and preservice teachers’ understanding and use of these definitions.

Quadrilaterals are rich constructs to study definitions. Quadrilaterals’ richness can be attributed to their being foundational in measurement, studying geometric properties as well as understanding the addition of complex numbers and vectors (Usiskin & Griffin, 2008). On the other hand, it is internationally recognised that defining and classifying quadrilaterals can be challenging for learners (e.g., pupils, preservice teachers) due to their reliance on prototypical shape images rather than definitions based on geometric properties (Fujita & Jones, 2007). This challenge influences preservice teachers (PTs), impacting their school practices (Jones et al., 2002). This study aims to explore PTs’ use of inclusive and exclusive definitions of quadrilaterals, using trapezium as a context. The research question we pursue is: What characterises preservice teachers’ use of inclusive and exclusive definitions of the trapezium in relation to other quadrilaterals?

Individuals interpret mathematical problem situations with their concept images and/or concept definitions. Concept images are “something non-verbal associated in our mind with the concept name […] a visual representation […] a collection of impressions or experiences” (Vinner, 2002, p.68), whereas concept definitions are the mathematical definitions of concepts specific to an individual. Furthermore, “referring to the formal definition is critical for a correct performance on given tasks ([…] identification of examples and non-examples of a given concept”) Vinner (2002, p.80). In making sense of PTs’ use of definitions, especially in geometry, we focused on two types of definitions: exclusive and inclusive (Usiskin & Griffin, 2008). Exclusive definitions of geometric figures are the definitions that lead individuals to understand those figures in isolation (e.g., rectangles are not part of the parallelogram set). In contrast, inclusive definitions allow the defined figures to include others (e.g., rectangles are part of the parallelogram set).

The use of inclusive definitions in teaching geometry is advantageous as it allows learners to better understand the interrelations among quadrilaterals (e.g., squares are part of the rectangle set) by focusing on how properties of one quadrilateral set satisfy the properties of another set. Interestingly, however, Usiskin and Griffin (2008) investigated mathematics textbooks published in the USA during the 1833-2008 period and found that only about 10% of these textbooks (n=8) used inclusive definitions and 90% (n=76) used exclusive definitions. Hence, if teachers align their teaching with the latter type of textbooks, they are more likely to miss the opportunity to help their pupils learn about the aforementioned interrelations when teaching geometry.

To what extent teachers are aware of different types of definitions and their advantages or disadvantages in teaching geometry is not known well in the research literature (Sinclair et al., 2016) even though it is valued universally. Our research focuses on PTs’ use of inclusive and exclusive definitions in the context of defining trapeziums. Although this study took place in Scotland, it will provide insights into teachers’ use of definitions that can inform mathematics education researchers in Europe and other countries.


Methodology, Methods, Research Instruments or Sources Used
The study participants were from a tightly structured one-year-long initial teacher education programme at the University of Glasgow. The programme prepares PTs to teach in Scottish primary schools. These teachers have a first degree (not necessarily in mathematics), as Scottish primary teachers are generalists and are expected to teach all curricular subjects.
One hundred forty PTs from the 2021-2022 cohorts were invited to complete an anonymous online questionnaire before they started their teacher education programme. The response rate was 50% (71 students). The questionnaire consisted of two sections; one focused on participants’ beliefs about and attitudes toward mathematics, and the other was on their understanding of the subject. This paper focuses on the latter section, which asks PTs to use the formal definitions of the trapezium taken from Usiskin and Griffin (2008) and to choose and justify which quadrilaterals (parallelogram, rectangle, rhombus, square, isosceles trapezium) fit those definitions:  

Definition #1: A trapezium is a quadrilateral with exactly one pair of parallel sides.
Definition #2: A trapezium is a quadrilateral with at least one pair of parallel sides.
a) If we accept Definition #1 which one of the following figure(s) would be considered as trapeziums? Please explain why.
b) If we accept Definition #2 which one of the following figure(s) would be considered as trapeziums? Please explain why.
c) If you were to use one of these definitions to teach students in your maths classes, which definition would you use? Please explain why.

We checked through participants’ responses for open-ended questions. We then generated categories out of those answers (e.g., no answer, correct, incorrect, partially correct, prototypical concept image, other) and then converted them into numeric codes for quantitative analysis (e.g., no answer=0, correct=1). We then used cross-tabulation (i.e., frequencies and percentages across relevant questions) and performed the Chi-square Test of Independence to explore the relationships among the answers given to the questions, using IBM SPSS 24.

Conclusions, Expected Outcomes or Findings
We found that 65% of the participants matched the exclusive definition of trapezium solely to isosceles trapezium and 57% linked the inclusive definition to all geometrical figures. Furthermore, 20% of the participants linked the exclusive definition and 29% linked the inclusive definition of trapezium to multiple geometrical figures. On the other hand, 15% could not connect the exclusive definition and 13% could not connect the inclusive one to any other geometric figure. 44% of the participants explained their choices correctly when applying the inclusive definition, whereas this proportion moves up to 64% for those providing correct justifications concerning the exclusive definition of a trapezium. There was a statistically significant association between the participants’ selection and justification of geometric figure(s) as a trapezium with an exclusive definition (χ^2(4, 94) = 170.16, p < .001 with a strong effect size of Cramer’s V = .95 (Cohen, 1988)) and with an inclusive definition (χ^2(8, 94) = 108.72, p < .001 with a strong effect size of Cramer’s V = .76 (Cohen, 1988)).
Most participants (64%) justified why the given shape(s) would be considered trapeziums by operating from a prototypical image as follows:
PT52: Only the trapezium and the isosceles trapezium have one set of parallel lines as the left, and right lines would meet if they were to continue on.
This suggests that their judgments are impacted by a prototypical (concept) image of an (isosceles) trapezium for exclusive definition.
To conclude, participants were more likely to operate with the exclusive definition of a trapezium when analysing the given geometric figures, rather than the inclusive definition requiring a concept definition geared by geometric properties.  Our findings support previous research (e.g., Fujita, 2012) indicating that most learners, even high-achievers, rely heavily on the prototypical examples of quadrilaterals and thus fail to understand the inclusion relations.

References
Clements, D. H., & Sarama, J. (2011). Early childhood teacher education: The case of geometry. Journal of Mathematics Teacher Education, 14(2), 133–148.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd Ed.). Lawrence Erlbaum Associates.
Delaney, S. (2012). A validation study of the use of mathematical knowledge for teaching measures in Ireland. ZDM - The International Journal on Mathematics Education, 44(3), 427–441.
Fujita, T., & Jones, K. (2007). Learners’ understanding of the definitions and hierarchical classification of quadrilaterals: Towards a theoretical framing. Research in Mathematics Education, 9(1), 3-20.
Fujita, T. (2012). Learners’ level of understanding of the inclusion relations of quadrilaterals and prototype phenomenon. Journal of Mathematical Behavior, 31(1), 60–72.
Jones, K., Mooney, C., & Harries, T. (2002). Trainee primary teachers’ knowledge of geometry for teaching. Proceedings of the British Society for Research into Learning Mathematics, 22(2), 95–100.
Sinclair, N., Bartolini Bussi, M. G., de Villiers, M., Jones, K., Kortenkamp, U., Leung, A., & Owens, K. (2016). Recent research on geometry education: An ICME-13 survey team report. ZDM Mathematics Education, 48(5), 691-719. https://doi.org/10.1007/s11858-016-0796-6
Usiskin, Z., & Griffin, J. (2008). The classification of quadrilaterals: A study of definition. Information Age Publishing.
Vinner, S. (2002). The role of definitions in the teaching and learning of mathematics. In D. Tall, D. (Ed.), Advanced Mathematical Thinking (Vol. 11, pp.65-81). Springer. https://doi.org/10.1007/0-306-47203-1_5
Zazkis, R., & Leikin, R. (2008). Exemplifying definitions: A case of a square. Educational Studies in Mathematics, 69, 131–148. https://doi.org/10.1007/s10649-008-9131-7


10. Teacher Education Research
Paper

Exploring Mathematics Anxiety and Attitude among Student Teachers in the First Year of their Initial Teacher Training

Su Kler1, Christos Dimitriadis1, Ruth Wood1, Sali Hammad2

1Kingston University, United Kingdom; 2International University for Science and Technology in Kuwait

Presenting Author: Kler, Su; Dimitriadis, Christos

This study aims to understand the relationships between mathematics anxiety, attitude, experience and choice of subject specialism among primary student teachers in the first year of their initial teacher training (ITT). During an ITT course at a London University, elements of anxiety and negative attitude surrounding mathematics were observed by tutors among trainee teachers. For example, some demonstrated a reluctance to actively participate in mathematics-related sessions or expressed concerns about their ability to teach mathematics, particularly with older and/or more able primary-aged students. Furthermore, at the end of the first year, students appeared to prefer other subjects to mathematics when they were required to select a subject specialism. Such observations are not unusual or new. Since the 1980s (Beilock et al., 2010; Cockcroft,1982; Ernest,1988; Hembree,1990), student teachers’ fear, anxiety, and negative attitudes towards mathematics have been highlighted as problematic with recommendations that training institutions should help students develop positive attitudes to and confidence in the subject (Cockcroft,1982).

To help prospective primary school practitioners develop positive attitudes and confidence during their ITT course, it is important to understand the learning experiences of students undertaking the course before their arrival on the ITT programme and their existing mathematics anxiety levels and attitudes to mathematics. During the programme, their attitude to mathematics as both teacher and learner may change; this research aims to critically analyse students’ experiences and mathematics anxiety. At the time of writing this, limited research exploring mathematics anxiety and the teaching of mathematics among primary student teachers is available; this research, therefore, seeks to contribute to understanding in this area.

Global interest in mathematics anxiety has been evident in the volume of research conducted and published over the last three decades. Such research often provides evidence that mathematics anxiety is associated with various negative cognitive and emotional outcomes (e.g. Ashcraft & Krause, 2007; Espino et al., 2017). Impact on cognitive outcomes is evidenced in low performance and achievement, mainly because anxiety interferes with the ability to maintain and manipulate information and resources within the mind, which is necessary for arriving at solutions in arithmetic calculations and problem-solving (Ashcraft & Krause, 2007). Emotionally, mathematics anxiety is associated with disliking and avoiding and possessing an unfavourable attitude towards mathematics, which, in turn, may impact achievement and eventually mathematical progress as well as career and course-related decisions that shape people’s future (Espino et al., 2017). Although most studies agree that there is no difference in the prevalence of mathematics anxiety between teachers and non-teachers (Barroso et al., (2021), there is evidence suggesting it is more prevalent among primary student teachers than in other sectors (Hembree, 1990). Research also indicates that formal mathematics instruction experiences influence this anxiety (Brady & Bowd, 2005). Generally, teachers anxious about mathematics have poor attitudes and perpetuate their anxiety and negative attitudes towards mathematics among their students (McAnallen, 2010). However, the relationships described above are not simple. Recent research, for example, suggests that the relationship between mathematics anxiety and mathematics performance is not unidirectional but rather bidirectional. Mathematics anxiety has a negative impact on performance, but poor mathematics performance may also increase anxiety (Carey et al., 2017; Maloney, Risko, Ansari, & Fugelsang, 2011). These are important observations as an established bidirectional relationship that concerns performing or teaching mathematics will exacerbate any impact and adverse outcomes for both ends, turning it into a vicious cycle.


Methodology, Methods, Research Instruments or Sources Used
This study adopts a mixed-method research design. The setting is the first year of a Qualified Teacher Status Primary Bachelor of Arts (Hons) programme at a London University, where student teachers attend taught sessions at the university and have placements at schools for teaching experience. Data were collected from Year 1 students over two consecutive academic years to identify patterns among different groups of students experiencing the same training provision. All 47 students were invited to complete an electronic questionnaire before undertaking their school placement and again after their placement, and to participate in individual semi-structured interviews. In the first year (the second is underway), 20 students completed the first questionnaire and 14 of them the second, and three participated in the interviews.
The two questionnaires consisted of five parts. The first three parts were the same for both questionnaires. They included measurement scales/inventories developed, validated and used in the past by other researchers to measure mathematics anxiety, attitudes to mathematics and attitudes to the teaching of mathematics. Part I measured mathematics anxiety using Hopko et al.’s (2003) nine-item Abbreviated Math Anxiety Scale (AMAS). Part II measured attitudes towards mathematics using Lim and Chapman’s (2013) 19-item scale of the short Attitudes Toward Mathematics Inventory (short ATMI). Part II also measured attitudes to teaching mathematics using three scales from Nisbet’s (1991) Attitudes to Teaching Mathematics Questionnaire (ATMQ) (14 items) specific to confidence and enjoyment, desire for recognition and pressure to conform. Part IV explored students’ experiences from formal mathematics instruction as learners in primary and secondary school (first questionnaire) and experiences from their first year of their ITT (the second questionnaire). Questions for Part IV had been adapted from Brady and Bowd’s (2005) questionnaire, which used closed and open questions to measure the mathematics experiences of pre-service education students. The semi-structured interviews aimed to explore in more depth participants’ experiences in addition to their beliefs/feelings about mathematics.
We used descriptive and non-parametric statistical tests to analyse the data from the questionnaires. Descriptive statistics helped us identify patterns among the data, and non-parametric tests consisting of calculations of Pearson correlation coefficients helped us determine the relationship between respondents’ total measuring scores from AMAS, short ATMI, ATMQ, and the other variables (e.g. experiences and choice of specialism). Internal consistency was measured using Cronbach’s Alpha. We analysed the interview data thematically (Opie & Brown, 2019) and utilised nVivo for coding and categorising.

Conclusions, Expected Outcomes or Findings
The following are preliminary conclusions based on the initial analysis of the first phase.
Most students who responded to the first questionnaire displayed high/middle anxiety levels. The gap between those with low anxiety and the rest of the respondents was considerable, making these students appear as a distinct group. Attitudes towards mathematics and attitudes towards teaching mathematics were mostly rated middle. Analysis of both questionnaires showed interesting relationships between mathematics anxiety, attitudes to mathematics and attitudes to teaching mathematics and the other variables examined. The anticipated negative correlation between mathematics anxiety and attitudes to mathematics was confirmed mainly for students with low anxiety. Relationships between mathematics anxiety and attitudes towards teaching mathematics were more complex, with some low-anxiety students displaying positive attitudes and high-anxiety students having mixed attitudes across the range (low to high). Complex relationships were also evident between mathematics anxiety and choosing mathematics as a subject specialism, with weak or insignificant correlations. Negative correlations were also observed between mathematics anxiety and qualification level or mathematics grade and between mathematics anxiety and experiences from compulsory education (low/high levels of liking/enjoying mathematics). Stronger relationships with significant negative correlations were observed between mathematics anxiety and attitudes to mathematics and mathematics anxiety and experiences from formal mathematics instruction.
The interviews confirmed the strong correlations between mathematics anxiety, attitudes to mathematics and experiences we observed in both questionnaires, including experiences acquired during the ITT programme. The weak correlation between mathematics anxiety and choice of specialism was also confirmed during the interviews. It seems that the choice of specialism was influenced more by the experiences students gained through the ITT programme: the mathematics seminars, the teaching during school placement and the support they had from their mentors, rather than the experiences acquired before commencing the ITT and their anxiety levels.

References
Ashcraft, M. H., Krause, J. A., (2007). Working memory, math performance, and math anxiety. Psychonomic Bulletin & Review, 14(2), 243-248.
Barroso, C., Ganley, C. M., McGraw, A. L., Geer, E. A., Hart, S. A., & Daucourt, M. C. (2021). A meta-analysis of the relation between math anxiety and math achievement. Psychological Bulletin, 147(2), 134. https://doi.apa.org/doi/10.1037/bul0000307
Beilock, S. L., Gunderson, E. A., Ramirez, G., & Levine, S. C. (2010). Female teachers’ math anxiety affects girls’ math achievement. Proceedings of the National Academy of Sciences, 107(5), 1860-1863. https://doi.org/10.1073/pnas.0910967107
Brady, P., & Bowd, A. (2005). Mathematics anxiety, prior experience and confidence to teach mathematics among pre‐service education students. Teachers and teaching, 11(1), 37-46. https://doi.org/10.1080/1354060042000337084
Carey, E., Hill, F., Devine, A., & Szűcs, D. (2017). The modified abbreviated math anxiety scale: a valid and reliable instrument for use with children. Frontiers in Psychology, 8(11). https://doi.org/10.3389/fpsyg.2017.00011
Cockcroft, W. H. (1982). Mathematics counts report of the Committee of Inquiry into the Teaching of Mathematics in Schools. HMSO.
Ernest, P. (1988, July). The attitudes and practices of student teachers of primary school mathematics. In Proceedings of 12th International Conference on the Psychology of Mathematics Education, Hungary (Vol. 1, pp. 288-295). Veszprém: OOK.
Espino, M., Pereda, J., Recon, J., Perculeza, E., & Umali, C. (2017). Mathematics anxiety and its impact on the course and career choice of grade 11 students. International Journal of Education, Psychology and Counselling, 2(5), 99-119. http://www.ijepc.com/PDF/IJEPC-2017-05-09-08.pdf
Hembree, R. (1990). The nature, effects, and relief of mathematics anxiety. Journal for Research in Mathematics Education, 21(1), 33-46. https://doi.org/10.2307/749455
Hopko, D., Mahadevan, R., Bare, R., & Hunt, M. (2003). The Abbreviated Math Anxiety Scale (AMAS): Construction, validity, and reliability. Assessment, 10(2), 178-82. https://doi.org/10.1177/1073191103010002008
Lim, S. Y., & Chapman, E. (2013). Development of a short form of the attitudes toward mathematics inventory. Educational Studies in Mathematics, 82(1), 145-164. https://doi.org/10.1007/s10649-012-9414-x
Maloney, E. A., Ansari, D., & Fugelsang, J. A. (2011). The effect of mathematics anxiety on the processing of numerical magnitude. The Quarterly Journal of Experimental Psychology, 64(1), 10-16. https://doi.org/10.1016/j.cognition.2009.09.013
McAnallen, R. R. (2010). Examining Mathematics Anxiety in Elementary Classroom Teachers https://www.proquest.com/docview/883120559
Nisbet, S. (1991). A new instrument to measure pre-service primary teachers’ attitudes to teaching mathematics. Mathematics Education Research Journal, 3(2), 34-56. https://doi.org/10.1007/BF03217226  
Opie, & Brown, D. (2019). Getting started in your educational research: design, data production and analysis. SAGE.


10. Teacher Education Research
Paper

360-degree Video as a Tool for Reflective Practice with Pre-service Teachers of Mathematics

Lisa O'Keeffe, Amie Albrecht, Bruce White

University of South Australia, Australia

Presenting Author: Albrecht, Amie

The importance and value of formative assessment for improving learning is widely accepted. This is true for student learning (Black & Wiliams, 2009) and for in-service teacher continued growth and development (Yorke, 2003). Formative assessment with teachers creates opportunities for teachers to explore student understanding (Yorke, 2003). Such opportunities are centred on the idea of teachers as reflective practitioners, enabling them to better tailor their own teaching practice to make progressive improvements (López-Pastor and Sicilia-Camacho, 2017). The bringing together of formative feedback and reflective practice is now well established as useful for teacher development, as is the use of video to support teacher reflection.

Video has been used in teacher education since the 1960s in a variety of ways. Examples include using video for lesson analysis (Santagata, 2014), for teacher professional development (Sherin, 2004), as a prompt for discussion between teachers (Borko et al., 2008), and to create professional learning communities (Sherin, 2004; van Es, 2012). Video can be viewed as both a ‘representation of practice’ and a powerful tool for the ‘decomposition of practice’, that is, breaking the teaching into parts to enable others or oneself to focus on particular elements (Grossman et al., 2009 p. 2064). A key enabler of video as a tool for reflection in teaching is that enables the educator to become more analytical in their reflections. It does so by removing the cognitive overload of ‘in-the-moment’ decision making (Rich & Hannafin, 2009) freeing the educator to reflect on the teaching and learning interactions. This confirms Girardet’s (2018) finding that video reflection can support the development of both the analytical and reflective abilities of teachers.

In our research we bring together the elements of formative assessment, teacher reflection, and video as a tool for reflective practice to explore ways pre-service teachers (PSTs) can be supported to better understand their own practice (O’Keeffe & White, 2021, 2022). Girardet (2018), among others, reminds that video observation of teaching practices (observation of oneself or others) can support the development of analytical and reflective abilities. Detailed and systematic observation of specific practices of the teacher in classroom promotes the development of the so-called ‘professional vision’ (Goodwin, 1994), that is, the ability to notice and interpret significant features of classroom interactions.

While much video-reflection research to date has been conducted with ‘regular’ flat video, we use 360-degree video (Balzarettia et al, 2019). We argue that 360-degree video mediates the process of teacher reflection more effectively than regular video because it provides greater capacity for the user (pre-service or in-service teacher) to focus and re-focus their reflection as needed (by panning around the screen/recording) while watching back or reviewing a recording. 360-degree video allows PSTs to experience video-recorded lessons from an immersive 360-degree perspective, providing a greater understanding of the entire context in which an interaction or an action is situated. For example, an interaction mis-remembered or not observed can be reviewed from multiple perspectives after the event —nothing is ‘off-camera’.


Methodology, Methods, Research Instruments or Sources Used
The PSTs who participated in this research are in their first semester of the first year of their teacher education program and in general have no formal teaching experience. As part of their course assessment, each student is paired with a pre-assigned partner to co-plan a mathematics lesson aimed at middle school students. Each pair then independently enacts the same element of their plan (usually the launch) to a cohort of their peers. These enacted lessons are recorded using 360-degree cameras, the recordings of which are shared with PSTs through a staged review and reflect process.

In this paper we discuss a case study of one pair of students.  We draw on their reflections of their own practice and that of their partner’s to form initial understandings of what the data means in regard to the following questions.
1. How can reflection on one’s own practice, using 360-degree video, inform one’s own future teaching practice?
2. How can reflection on a co-planner’s practice, using 360-degree video, inform one’s own future teaching practice?

PSTs completed a post-reflection after each ‘teaching experience’. These reflections were analysed using an interpretative phenomenological analysis (IPA).  A key function of IPA is that the “overall outcome for the researcher should be a renewed insight into the ‘phenomenon at hand’ - informed by the participant’s own relatedness to, and engagement with, that phenomenon” (Larkin et al., 2006, p. 117).  Hence, IPA was chosen as the intention of the research was to better understand the lived experiences of the PSTs, and IPA focuses on each case independently before seeking to identify commonalities across the data.

Conclusions, Expected Outcomes or Findings
The initial data analysis points to the way video reflection supports PSTs to see their own development and growth as a teacher, demonstrating greater self-awareness of areas for further development. This self-awareness became more evident when they reflected on each other’s enacted practice.

Using 360-degree video to reflect on their partner’s enacted lesson proved useful to both PSTs. Sarah (pseudonym) talks about trying to understand the approach her partner took. She described how they planned the same lesson together, but their enacted lessons were vastly different. When reflecting on what she learned about her own teaching from watching Jake’s (her co-planning partner) lesson she indicated that “merely giving questions to the students may not help in explaining the purpose. Calling students to the board may also help with improving learning” (which Jake had modelled).

Similarly, Jake was also surprised that, despite planning with Sarah, his enacted lesson was very different, “It was extremely interesting to see how differently the same lesson plan was enacted ... the contrast in instruction style and structure helped me reflect on what teaching approach I feel is the best way for me personally”. Jake also offered an insightful reflection as to what he learned about himself as a teacher, “While watching my partners video, I was struck with the thought that, if I were a student, I would have had a better learning experience sitting through my own presentation. This is of course a biased view, but what I realized is that the model of teaching that I perform is based on, subconsciously, what I would want as a student.  ….. I think what works for me would be a good starting point, being easier for me to plan and model, but I should be very willing to critically reflect and adjust for my students’ needs.”

References
Balzarettia, N., Cianib, A., Cutting C., O’Keeffe, L.  & White, B. (2019). Unpacking the potential of 360degree video to support preservice teacher development. Research on Education and Media. 11 (1), 63-69.
Black, P. & Wiliam, D (2009). Developing the theory of formative assessment Educational Assessment, Evaluation and Accountability. 21 (1), pp. 5-31,
Borko, H., J. Jacobs, E. Eiteljorg and Pittman, M. E. (2008). Video as a tool for fostering productive discussions in mathematics professional development. Teaching and Teacher Education, 24(2), 417-436.
Girardet. C.  (2018) Why do some teachers change and others don’t? A review of studies about factors influencing in-service and pre-service teachers’ change in classroom management. Review of Education. 6 91), 3-36.
Goodwin, C. (1994). Professional vision. American Anthropologist, 96(3), 606-633.
Grossman, P., Compton, C., Igra, D., Ronfeldt, M., Shahan, E., & Williamson, P. (2009). Teaching practice: a cross-professional perspective. Teachers College Record. 111, 2055–2100.
Larkin, M. Watts, S.& Clifton, E. (2006). Giving voice and making sense in interpretative phenomenological analysis. Qualitative Research in Psychology. 3, 102-120.
López-Pastor, V. & Sicilia-Camacho, A. (2017). Formative and shared assessment in higher education. Lessons learned and challenges for the future. Assessment and Evaluation in Higher Education, 42, 77-97,
O’Keeffe, L. & White, B. (2021) Supporting pre-service teachers of mathematics to ‘notice’. In Y. H. Leong, B. Kaur, B. H. Choy, J. B. W. Yeo & S. L Chin (Eds.), Excellence in Mathematics Education: Foundations and Pathways (Presented at the 43rd annual conference of the Mathematics Education Research Group of Australasia), pp. 1-18. Singapore: MERGA.
O’Keeffe, L. & White, B. (2022). Supporting Mathematics pre-service teacher reflection with 360degree video and the knowledge quartet. Australian Journal of Teacher Education.
Rich, P. J. & Hannafin, M. (2009), Video annotation tools: Technologies to scaffold, structure, and transform teacher reflection. Journal of Teacher Education, 60(1), pp.52-67.
Santagata, R. (2014). Video and teacher learning: key questions, tool and assessment guiding research and practice. Beitraege zur Lehrerbildung, 32(2),196-209.
Sherin, M.G., 2004, New perspectives on the role of video in teacher education. In Using video in teacher education, Emerald Group Publishing Limited, pp. 1-27.
van Es, E. A. (2012). Examining the Development of a Teacher Learning Community: The Case of a Video Club. Teaching and Teacher Education: An International Journal of Research and Studies, 28(2), 182-192.
Yorke, M. (2003). Formative assessment in higher education: Moves towards theory and the enhancement of pedagogic practice. Higher Education, 45, 477-501.


10. Teacher Education Research
Paper

In the Abyss of Big Ideas: Preservice Teachers are Challenged in Planning Statistics Lessons

Per Blomberg1,2

1Halmstad University, Sweden; 2Karlstad University, Sweden

Presenting Author: Blomberg, Per

Introduction and research question

Pedagogical content knowledge (PCK), as coined by Shulman (1986), pays attention to the way of thinking about teacher knowledge and making a school subject understandable to others. An important concept within the PCK community is the notion of Big Ideas, which involves recognising fundamental principles that underpin the subject. Loughran et al. (2004) emphasised the significance of identifying Big Ideas as a crucial component of articulating one’s PCK. Additionally, Hurst (2019) emphasised that teachers must not only grasp Big Ideas but also understand how these selected concepts interconnect. Furthermore, Chan et al. (2019) highlighted appropriate selection, connection, and coherence of Big Ideas as the first-ordered rubric for measuring the quality of PCK. This paper answers researchers’ calls for further exploration of the fundamental principles underlying the teaching of statistics (Watson et al., 2018). The research aim is to examine how preservice teachers (PTs) select and connect Big Ideas when designing a lesson sequence dedicated to statistics instruction in primary school.

According to Charles (2005), “A Big Idea is a statement of an idea that is central to the learning of mathematics, one that links numerous mathematical understandings into a coherent whole” (p. 10). This definition can be applied to the domain of statistics: A statistical Big Idea represents a statement of an idea central to learning statistics, and connects different statistical concepts and methods into a coherent structure. The findings in this paper are drawn from an ongoing multi-year educational design research aimed at supporting the development of PTs’ PCK in teaching statistical inference (Blomberg, 2022). One research question that has been explored refers to the impact of a reflection and planning tool on the outcome of the PTs’ lesson planning. In the search for potential design principles, I conjectured that predefining Big Ideas in the reflecting and planning tool would enhance the quality of the PTs’ outcomes, particularly regarding their understanding and interconnections of Big Ideas.

Conceptual framework

A recent addition to the PCK research field is the Refined Consensus Model (RCM), developed by Carlson et al. (2019). Unlike previous PCK theories, RCM embraces a more dynamic perspective that acknowledges multiple dimensions of PCK and the exchange of knowledge between these dimensions. Central aspects of teachers’ professional knowledge encompass collective, personal, and enacted PCK, and their interconnections with professional knowledge bases such as content knowledge, curricular knowledge, and pedagogical knowledge. For instance, enacted PCK encompasses activities like instructional planning, teaching, and reflection on teaching practices and student outcomes. To frame the present research and discern the elements under investigation, RCM has served as a background theory.

Within the discipline of statistics education, like the field of mathematics education, there is a noticeable range of perspectives regarding essential elements and ideas for statistical thinking and statistical literacy, and changes in practice are continually influencing them (Zieffler et al., 2018). In this study, I have employed a developed framework as a foreground theory to discern and characterise the outcomes of statistical Big Ideas among PTs. The framework is a combination of data modeling (Lehrer & Schauble, 2004) and informal statistical inference (ISI) (Makar & Rubin, 2009). The components of the statistical inference modeling framework (SI modeling) can be summarised as follows: (a) posing statistical questions within meaningful contexts, emphasising variability through real-world problems; (b) generating, selecting, and measuring attributes that exhibit variation in relation to the posed questions; (c) collecting first-hand data, prompting students to make decisions about investigation design; (d) representing, structuring and interpreting sample and sampling variability; and (e) engaging in informal inferences based on these processes and the interconnectedness of these ideas.


Methodology, Methods, Research Instruments or Sources Used
Research inquiries and conjectures in this project are addressed through the implementation of iterative classroom-based investigations, drawing inspiration from the field of educational design research (e.g., Bakker, 2018). Employing a design research methodology enables us to develop better teaching-learning strategies to improve the PTs’ teaching. To capture and document PTs’ significant concepts, we utilise a research-based reflective instrument known as Content Representation (CoRe). The CoRe template, devised by Loughran et al. (2004), serves as a valuable tool for researchers to document research participants’ PCK. At the core of the CoRe template lies its capacity to represent the user’s PCK of the specific subject matter. Initially, the formulation of Big Ideas revolves around a selected theme, followed by addressing PCK-related questions to these chosen Big Ideas.

This paper focuses on the PTs selected Big Ideas and their answers to the first question: What do you expect the students to learn about this specific knowledge? The empirical data analysed in this study have been generated in the context of PTs collaborating in groups to plan a hypothetical lesson about statistics. During this planning phase, personal PCK was transformed into enacted PCK as articulable knowledge. Since the completed CoRe is the collective opinion from a group of preservice teachers, it can be assumed to represent a form of collective PCK for that group of PTs. The written outcomes of PTs’ collectively completed CoRe have been analysed with a content analysis approach (Robson & McCartan, 2017). The SI modeling framework has been used as operationalised categories to analyse the outcomes mediated by the CoRes.

Four sub-studies have been carried out in the context of PTs education between 2021 and 2022. The research team consisted of one researcher/teacher educator (the same as the author) in collaboration with two to three teacher educators. Each sub-study was carried out with a group of PTs focused on becoming teachers for students aged 6–12 years. These PTs were introduced to the idea of PCK and the framework of CoRe as a valuable PCK tool that offers a way to plan for learning and teaching. In groups of 3-4, they were tasked to plan a hypothetical statistics lesson sequence by taking three Big Ideas as a starting point. For further details, see Blomberg (2022).

Conclusions, Expected Outcomes or Findings
The findings from the first two sub-studies draw attention to the challenge of preparing PTs to plan and teach inferential statistics. In short, the first sub-study showed that the PTs’ outcomes clearly emphasised compiling and organising data, interpreting data, and being statistically literate. The PTs’ outcomes regarding inference were almost non-existent, and nearly half of the participating groups highlighted topics from statistical contexts, separate from statistics, as Big Ideas. The second sub-study showed similar findings. Although these PTs were lectured on the measure of distribution and statistical inference, no apparent traces of these big ideas could be found in the results of their completed CoRes.

A conclusion from the first two sub-studies points to the need to accommodate the diversity of statistical Big Ideas mediated by CoRes. Otherwise, PTs run the risk of leaving teacher education without any PCK experience of essential statistical Big Ideas (e.g., statistical question, distribution, and statistical inference) and how these Big Ideas are connected. Therefore, an improved teaching-learning strategy was desirable and has been conducted in the sub-studies 3 and 4. A hypothetical design principle tested in study 3 was that reducing the degrees of freedom offered by CoRes can improve the quality of PTs’ findings of Big Ideas and their connections. However, the findings from the last two sub-studies indicate that reducing the degrees of freedom by preparing the CoRe with predefined Big Ideas is an insufficient intervention change. In addition, PTs should be offered specialised knowledge of the relevant learning content and be supported by expert guidance by, for example, providing feedforward on their completed CoRes.

Beyond findings in terms of teaching-learning strategies and PCK measurement to support teacher educators, this current work may also contribute methodologically and empirically to the ongoing discussion in collaborative teacher education research.

References
Bakker, A. (2018). Design research in education: A practical guide for early career researchers (1 ed.). Routledge. https://doi.org/10.4324/9780203701010
Blomberg, P. (2022). Learning opportunities for pre-service teachers to develop pedagogical content knowledge for statistical inference Proceedings of the Twelfth Congress of the European Society for Research in Mathematics Education (CERME12), Free University of Bozen-Bolzano and ERME. https://hal.science/CERME12/search/index/?q=%2A&domain_t=math
Carlson, J., Daehler, K. R., Alonzo, A. C., Barendsen, E., Berry, A.., . . . Wilson, C. D. (2019). The Refined Consensus Model of Pedagogical Content Knowledge in Science Education. In A. Hume, R. Cooper, & A. Borowski (Eds.), Repositioning Pedagogical Content Knowledge in Teachers’ Knowledge for Teaching Science (pp. 77-94). Springer Singapore. https://doi.org/10.1007/978-981-13-5898-2_2
Chan, K. K. H., Rollnick, M., & Gess-Newsome, J. (2019). A Grand Rubric for Measuring Science Teachers’ Pedagogical Content Knowledge. In A. Hume, R. Cooper, & A. Borowski (Eds.), Repositioning Pedagogical Content Knowledge in Teachers’ Knowledge for Teaching Science (pp. 251-269). Springer Singapore. https://doi.org/https://doi.org/10.1007/978-981-13-5898-2_11
Charles, R. I. (2005). Big Ideas and Understandings as the Foundation for Elementary and Middle School Mathematics. Journal of Mathematics Education Leadership, 7(3), 9-24. https://jaymctighe.com/wp-content/uploads/2011/04/MATH-Big-Ideas_NCSM_Spr05v73p9-24.pdf
Hurst, C. (2019). Big Ideas of primary mathematics: It’s all about connections! In T.-L. Toh & J. Yeo (Eds.), Big Ideas in Mathematics: Yearbook 2019, Association of Mathematics Educators (pp. 71-93). World Scientific Publishing Co Pte Ltd. https://doi.org/10.1142/11415
Lehrer, R., & Schauble, L. (2004). Modeling Natural Variation Through Distribution. American Educational Research Journal, 41(3), 635–679. https://doi.org/10.3102/00028312041003635
Loughran, J., Mulhall, P., & Berry, A. (2004). In search of pedagogical content knowledge in science: Developing ways of articulating and documenting professional practice. Journal of Research in Science Teaching, 41(4), 370-391. https://doi.org/10.1002/tea.20007
Makar, K., & Rubin, A. (2009). A Framework for Thinking about Informal Statistical Inference. Statistics Education Research Journal, 8(1), 82–105. https://doi.org/10.52041/serj.v8i1.457
Robson, C., & McCartan, K. (2017). Real world research (4 ed.). John Wiley & Sons.
Shulman, L. S. (1986). Those Who Understand: Knowledge Growth. Educational Researcher, 15(2), 4-14. https://doi.org/10.3102/0013189x015002004
Watson, C., Fitzallen, N., Fielding-Wells, J., & S., M. (2018). Statistics Education Research. In D. Ben-Zvi, K. Makar, & G. J. (Eds.), International Handbook of Research in Statistics Education (pp. 105-138). Springer International Publishing. https://doi.org/10.1007/978-3-319-66195-7
Zieffler, A., Garfield, J., & Fry, E. (2018). What Is Statistics Education? In D. Ben-Zvi, K. Makar, & J. Garfield (Eds.), International Handbook of Research in Statistics Education (pp. 37-70). Springer International Publishing. https://doi.org/10.1007/978-3-319-66195-7_2


 
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