To gain a better understanding of beginning secondary science teachers’
knowledge and practices of metacognition and their use of metacognitive teaching practices, I conducted this study using two approaches. First, I employed a quantitative design, including administering a survey to describe participants’ knowledge or
awareness of metacognition, analyzing quantitative data using a linear regression to find variables that could affect knowledge of metacognition, and using coded classroom observations as part of a larger research study. Second, I utilized a qualitative design to interview teachers in order to analyze their understanding of metacognition and practices of and for metacognition (experiences and metacognitive teaching), as well as conducting classroom observations and artifact analysis. I describe the findings using the research questions that framed the project. I have bolded some sentences and words in the participants’ excerpts to highlight important ideas within those vignettes.
Research Question #1:
What is Beginning Secondary Science Teachers’ Understanding of Metacognition?
To answer this question, I used qualitative and quantitative approaches and their associated data analysis. I will first present the quantitative analysis to describe beginning secondary science teachers’ knowledge or awareness of metacognition and variables that might affect metacognitive awareness. To describe participants’ understanding of
metacognition and practices, I used qualitative data from the semi-structured interviews. More specifically, the question asks: to what extent are these teachers aware, or
unaware, of their knowledge of metacognition? To answer this question, I used the MAIT
98 The sample included 36 participants, of which 8% were first-year teachers or
teachers with no prior experience, 36% were second-year teachers or teachers with one year of experience, 28% had three years of experience, and 17% had four years of experience. 36% percent of participants reported teaching one subject (e.g., biology, chemistry, general science, or ESS) during the time they answered the MAIT survey, while 64% reported teaching more than one subject. Participants revealed they were teaching a range of science subjects in secondary education (Table 4.1), the most common of these being biology (30%), physics (24%), and chemistry (16%). Table 4.1
Subjects Taught by Participants during Fall 2016
Subject*
Biology (%) Chemistry (%) Physics (%) ESS (%) Other** (%)
First-year teachers (n=3) 20 20 40 0 20
Second-year teachers (n=13) 33 12.5 25 17 12.5
Third-year teachers (n=4) 12.5 25 25 12.5 25
Fourth-year teachers (n=10) 36 18 18 14 14
Fifth-year teachers (n=6) 27 9 27 18 18
Total science teachers (n=36) 30 16 24 14 16
* A teacher could teach more than one subject. 36% of teachers were teaching one subject during fall 2016 and 64% two or more different subjects.
** Other courses: general science (middle school), elective high school courses (e.g., forensic science, zoology, anatomy and physiology, psychology, microbiology).
Additionally, survey-takers were often teaching in more than two different content areas. For example, 39% of respondents reported teaching one course, while another 39% reported two different content areas (e.g., biology and chemistry or physical science and Earth and space science [ESS]). Moreover, 14% teachers reported teaching three different subject areas during Fall 2016 and 8% reported teaching more than four content areas. For example, one of the participants reported teaching biology or life science; physics or physical science chemistry; Earth and space science or geoscience,
99 and general science. Teachers in small schools often teach several science classes from different content areas.
Appendix L lists the means, standard deviation, modes, and percentages of teachers’ answers to the MAIT survey, based on Yousef Mai’s (2015) analysis protocol. The highest items included Item #15, “I use different teaching techniques depending on
the situation (conditional knowledge)” (M=4.4, SD=0.5); Item #2, “I try to use teaching techniques that worked in the past (procedural knowledge)” (M=4.3, SD=0.5); and Item #18, “After teaching a point, I ask myself if I’d teach it more effectively next time” (evaluation) (M=4.3, SD=0.6). For Item #2, the average increased as years of teaching experience increased. The average of first-year teachers for item #2 was 4.0, while fifth- year teachers’ average for the same item was 4.5. Teachers with more teaching
experience tended to use more strategies than first-year teachers and had greater awareness of strategies that worked or did not work.
Table 4.2
Knowledge of Metacognition and Metacognitive Regulation Average and Standard Deviation Based on MAIT Survey
Years of experience
Knowledge of metacognition M (SD) Metacognitive regulation M (SD) Declarative Procedural Conditional Planning Monitoring Evaluation 0 years (n=3) 4.1 (0.8) 3.8 (0.8) 3.8 (1.0) 3.5 (0.8) 3.8 (0.8) 3.7 (1.0) 1 year (n=13) 4.0 (0.6) 3.9 (0.7) 3.9 (0.8) 3.8 (0.7) 4.1 (0.6) 3.9 (0.6) 2 years (n=4) 4.1 (0.7) 3.9 (0.9) 4.0 (0.7) 3.6 (1.0) 4.0 (1.0) 4.0 (0.7) 3 years (n=10) 4.1 (0.6) 3.9 (0.6) 3.9 (0.7) 3.8 (0.7) 4.1 (0.6) 3.9 (1.0) 4 years (n=6) 4.1 (0.5) 4.1 (0.4) 4.0 (0.6) 3.8 (0.5) 4.0 (0.6) 4.1 (0.5) All (n=36) 4.1 (0.6) 3.9 (0.6) 3.9 (0.7) 3.7 (0.7) 4.0 (0.7) 3.9 (0.8)
The lowest items were #21, “I know when each teaching technique I use will be
most effective (conditional knowledge)” (M=3.2, SD=0.7); #24, “I ask myself if I have considered all possible techniques after teaching a point” (evaluation) (M=3.4, SD=0.9); and #10, “I set my specific teaching goals before I start teaching” (planning) (M=3.5,
100 SD=0.9). The mode of almost all items was 4, except item #21, which was 3.
Accordingly, first- and second-year teachers scored item #21 lower (M=2.7) than fifth- year teachers (M=3.5).
Overall, on a scale of 1 (disagree) to 5 (strongly agree), the survey-takers (n=36) scored a mean of 3.9 (SD=0.3) on the whole instrument. In terms of knowledge of
metacognition (Table 4.2), their declarative knowledge seemed steady from teachers with 0 to 4 years of experience, with a mean of 4.1 in almost all the groups. Procedural
knowledge slightly increased from Year 0 (M=3.8) to Year 4 (M=4.1); conditional knowledge also slightly increased from Year 0 (M=3.8, SD=1.0) to Year 4 (M=4.0, SD=0.6). The variability (i.e., standard deviation) of teachers’ answers decreased slightly
in almost all indicators from Year 1 to Year 4. This could mean that their declarative knowledge about metacognition did not increase over time, but years of experience helped them better understand how and when to use it. However, none of these changes were statistically significant.
In terms of metacognitive regulation, the lowest indicator was planning (M=3.7, SD=0.7). As in the knowledge of metacognition, years of experience seemed to have a slight influence on scores, with higher means in Year 4 than Year 0. Thus, teachers can plan, monitor, and evaluate their practices somewhat better after four years (and with less variability) than teachers with no experience. However, I needed more evidence to support this evidence. I concluded, then, that during the first five years of teaching, participants’ knowledge of metacognition might remain almost the same or slightly
101 Next, what variables could affect teachers’ metacognitive awareness? To answer this question, I first checked the internal reliability or consistency of the instrument. I used Cronback’s alpha for this purpose, obtaining a value of 0.808. As a rule of thumb,
values in this test between 0.9 and 0.8 are considered excellent. Therefore, the instrument offered excellent reliability and allowed me to use the MAIT average in the linear
regression analysis. I also conducted a diagnostic analysis to confirm that the data met the assumptions for the linear regression (Appendix M).
Figure 4.1 Linear regression scatterplot: years of experience on metacognitive awareness.
There is a slight positive linear relationship between these two variables, but it is not statistically significant.
After conducting a linear regression of years of experience on metacognitive awareness (MAIT survey results), I obtained a positive relationship between these
variables, R = 0.187. This means that as years of experience increased, the MAIT average scores increased as well (Figure 4.1), concurring with the hypothesis that with more years of experience teachers have more metacognitive awareness. The model for this sample was MAIT average = 3.853 + 0.041 (years of experience). This means that the intersect
3 3.2 3.4 3.6 3.8 4 4.2 4.4 4.6 0 1 2 3 4 5 M A IT s u rv ey ( av er ag e) Years of experience