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   Advancements in Agricultural Development 
  Volume 4, Issue 2, 2023 
  agdevresearch.org 

 

1. Margaret Reaves, Graduate Student, University of Florida, 408 Rolfs Hall, PO Box 110540, Gainesville, FL 32611, 

mreaves@ufl.edu,  https://orcid.org/0009-0004-3642-7812  
2. Bradley M. Coleman, Assistant Professor, Oklahoma State University, 445 Agricultural Hall, Stillwater, OK 74078, 

b.coleman@okstate.edu,  https://orcid.org/0000-0001-5981-5747 
3. Carla B. Jagger, Assistant Professor, University of Florida, 307B Rolfs Hall, PO Box 110540, Gainesville, FL 32611, 

carlajagger@ufl.edu,  https://orcid.org/0000-0001-9796-6271  
4. J.C. Bunch, Associate Professor, University of Florida, 307A Rolfs Hall, PO Box 110540, Gainesville, FL 32611, 

bunchj@ufl.edu,  https://orcid.org/0000-0001-8729-2349 
5. Glenn D. Israel, Professor Emeritus, University of Florida, 305 Rolfs Hall, PO Box 110540, Gainesville, FL 32611, 

gdisrael@ufl.edu,  https://orcid.org/0000-0002-1328-0262  
91 

 

Examining Preservice Teachers’ Perceived Performance While 
Student Teaching: A Longitudinal Study 

 
M. Reaves1, B. M. Coleman2, C. B. Jagger3, J. C. Bunch4, G. D. Israel5 

 
 

Article History 
Received: March 23, 2023 
Accepted: May 30, 2023 
Published: June 14, 2023 
 
 
Keywords 
agricultural education; self-regulated 
learning; self-reflection 
  

Abstract 
With this study, we sought to fill a gap regarding preservice teachers’ self-
evaluation during the student teaching experience. An instrument was 
created and validated for use as a weekly self-evaluation tool for 
preservice teachers during the student teaching internship. This 
instrument encourages preservice teachers to self-assess and use self-
regulated learning strategies during their student teaching experience. 
The finalized instrument should be used in conjunction with other 
activities of the student teaching portfolio to meet the phases of self-
regulated learning (forethought, performance, and self-reflection). The 
purpose of this study was to examine the change in preservice teachers’ 
perceived performance over time during the 14-week student teaching 
internship. The objectives of this study were to describe preservice 
teachers’ performance scores and examine the variance in preservice 
teachers’ self-reported performance scores over the student teaching 
internship. Means and standard deviations for each of the five constructs 
during the 14-week period are reported. The self-evaluation scores of all 
five constructs of the validated instrument show an upward trend over 
the 14-week student teaching internship, with peaks and valleys 
scattered throughout. Research should continue with the goal of 
identifying the reasons for the peaks and valleys in weekly self-evaluation 
data. 

 



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Introduction and Problem Statement 
 
A student teaching internship is the capstone experience for many teacher preparation 
programs at universities. Lasting between ten and sixteen weeks, student teaching internships 
provide opportunities for preservice teachers to develop skills in classroom instruction, student 
management, lesson preparation, personal and professional growth, and reflection as an 
educator (Miller & Wilson, 2010). These opportunities for immersive learning experiences occur 
in a true classroom environment, which cannot be simulated easily in other ways (Coleman et 
al., 2021).  

The preservice teachers’ school placement and cooperating teacher are assigned by their 
university-based faculty coordinator. School placements and cooperating teachers are often 
assigned based on the growth areas needed by the preservice teacher, along with other factors. 
Throughout the student teaching internship, preservice teachers are expected to complete 
various self-assessments and activities that allow them to evaluate their own skill development. 

Repeated self-assessment is an important aspect of growth during the student teaching 
internship. Self-assessment occurs when students make judgements regarding their own 
learning and achievements, leading to self-regulated learning (Falchikov & Boud, 1989; Max et 
al., 2022; Panadero et al., 2016). Understanding how preservice teachers self-assess their ability 
in certain areas can help teacher educators better prepare preservice teachers for a student 
teaching internship and later career success. Through this study, we sought to validate a weekly 
self-evaluation instrument based on the Florida teaching standards in agricultural education 
and used this instrument to examine the change in preservice teachers’ perceived performance 
over time during the student teaching internship. 

Theoretical and Conceptual Framework 
 
Preservice teachers are expected to be self-regulated learners, and the structure of the student 
teaching internship encourages this expectation. Establishing the expectations of self-regulated 
learning early in the teacher preparation program encourages preservice teachers to 
acknowledge, hear, and listen to their own voice (Belenky et al., 1986; Collier, 1999). When 
included throughout the teacher education program, self-regulated learning techniques can 
help preservice teachers both to reflect on their academic performance and learn strategies to 
become more self-regulated students (Ganda & Boruchovitch, 2018). 

The cyclical process of self-regulated learning typically includes three phases: (a) forethought, 
(b) performance, and (c) self-reflection (Zimmerman, 2002). Moving through all three phases is 
important to engage in a quality educational experience. (Bembenutty, 2011; Ganda & 
Boruchovitch, 2018). In this study, it is assumed that preservice teachers considered each week 
of their student teaching internship to be a “performance” and completed the cyclical process 
as such. To fulfill the forethought phase of self-regulated learning, student teachers set goals 
each week and determined their strategies for achieving the goals. As they moved through the 
week of teaching (the performance phase) and interacting with students, preservice teachers 



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informally monitored their performance and self-assessed their progress towards achieving the 
goals they set for the week. At the end of the week, the preservice teacher completed the self-
evaluation instrument and reflected on their performance and used the results to guide their 
goal setting for the next week, participating in the self-reflection phase of the self-regulated 
learning cycle. Part of this self-reflection phase should have included the preservice teacher 
making self-judgements about their satisfaction and success (Ganda & Boruchovitch, 2018). 

Self-regulated learners are metacognitively, motivationally, and behaviorally active in learning 
environments (Zimmerman, 1989). As self-regulated learners, preservice teachers are often 
intrinsically motivated and take control of their own learning (Oates, 2019). A self-regulated 
learner may identify strategies to improve their understanding and monitor their learning, 
especially doing so without the encouragement of teachers, parents, and other instructional 
leaders (Zimmerman, 1989). Some self-regulated learning strategies that preservice teachers 
should pursue in a student teaching internship include (a) self-evaluating, (b) organizing and 
transforming, (c) goal setting and planning, (d) seeking information, (e) keeping records and 
monitoring, (f) rehearsing and memorizing, (g) seeking social assistance, and (h) reviewing 
records. (Ganda & Boruchovitch, 2018; Zimmerman, 1989). 

Self-regulated learning is not only an ideal approach for the student teaching internship but 
also for a future career in the educational field or otherwise (Ganda & Boruchovitch, 2018). 
Self-regulation should happen continually in the classroom and educational environment 
(Bembenutty, 2008; Dembo, 2001; Ganda & Boruchovitch, 2018). Preservice teachers can also 
practice teaching their own students this self-regulated learning process and strategies, helping 
to promote lifelong learning skills for all (Luftnegger et al., 2012; Oates, 2019). 

Purpose 
 
The purpose of this study was to validate an instrument (weekly self-evaluation form) based on 
the Florida teaching standards in agricultural education and use this instrument to examine the 
change in preservice teachers’ perceived performance over time during the student teaching 
internship. Three research objectives guided this study:  

1. Determine if constructs describing factors of performance are internally consistent.  
2. Determine if instrument items cluster into latent constructs that can be used to describe 

factors of performance.  
3. Describe preservice teachers’ performance scores over the 14-week student teaching 

experience. 
 

Methods 
 
This study was part of a larger research project (Coleman et al., 2021). The participants were 
chosen through single-stage, nonprobability convenience sampling. Each cohort of preservice 
teachers who were completing a student teaching internship through the University of Florida 
Department of Agricultural Education and Communication in the spring semesters of 2015–



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2019 were included in the study, yielding 81 participants. After removing 22 participants whose 
student teaching portfolios were missing or inaccessible, 59 participants remained. This study 
was completed longitudinally over the 14 weeks of each student teaching internship.  

All data were collected through a student teaching portfolio, which each participant completed 
as part of their internship requirements. The completed student teaching portfolio includes 12 
components: (a) pre-placement experiences, (b) teaching calendar, (c) placement experiences, 
(d) clock hour worksheet, (e) weekly reflection journal, (f) SAE visits, (g) case study, (h) mock 
interview, (i) weekly lesson plans, (j) weekly self-evaluation forms, (k) weekly cooperating 
teacher evaluation forms, and (l) university supervisor evaluation forms. 

Instrumentation 
The weekly self-evaluation form created to assess the preservice teachers’ perceived 
performance was adapted from the Florida Educator Accomplished Practices which are 
standards developed by the Florida Department of Education (Florida Department of Education, 
n.d.). University of Florida teacher education faculty from the Department of Agricultural 
Education and Communication adapted the Florida teaching standards into an instrument for a 
preservice teacher weekly performance self-evaluation. Since this was a newly developed 
instrument there was a need to determine if latent constructs existed within the modified 
preservice teacher self-evaluation form. Individual items were selected to develop an index to 
measure said constructs (Kumar Chaudhary & Israel, 2022). The modified instrument had 26 
items. One item, develops learning experiences that require students to demonstrate skills and 
competencies, was removed because more than half (52.9%) of the data were missing. The 25 
remaining items were confirmed to measure five latent constructs when the instrument was 
used by the cooperating teacher to evaluate their student teacher. Those constructs were (a) 
instructional design (five items), (b) instructional practice (six items), (c) student-centered 
teaching (four items), (d) teacher professionalism (five items), and (e) reflective and 
autonomous practitioner (five items) (Coleman et al., 2021). However, the purpose of this study 
is to confirm the constructs within the population of student teachers who used the instrument 
for self-evaluation.  

Data Analysis 
All data were analyzed using SPSS version 27. Descriptive statistics were used to summarize 
demographic data. The data were analyzed for the distribution of missingness (Schafer & 
Graham, 2002), and 37.4% (n = 19,482) of the values were missing at random. The proportion 
of missing data was considered to be relatively large (Schafer, 1999). Therefore, multiple 
imputation was conducted to address the missing values (Schafer & Graham, 2002; van Ginkel 
et al., 2020). Using the pooled results from the analysis of ten multiple imputed data sets, 
descriptive statistics (mean, standard deviation, frequency, and percentage) were used to meet 
the objectives of this study. Additionally, reliability analysis was conducted using Cronbach's 
alpha to check the internal consistency of each construct's items. Because the instrument was 
modified significantly, exploratory factor analysis (EFA) using principal axis factoring was used 
to analyze the relationship between variables (Floyd & Widaman, 1995).  



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Findings 
 
Objective 1: Determine if constructs describing factors of performance are internally 
consistent   
All five constructs exceeded the recommended alpha coefficient of .7 (DeVellis, 2012); 
therefore, the items were deemed reliable (Table 1). The Kaiser-Meyer-Olkin (KMO) measure of 
sampling adequacy was utilized to assess the suitability of the data for factor analysis. Results 
were inspected for a value of .6 or above (Kaiser, 1970, 1974). Further, Bartlett's test of 
sphericity was assessed for significance (p ≤ .05; Bartlett, 1954). The KMO measure of sampling 
adequacy and Bartlett’s test of sphericity are reported in Table 1. The Cronbach’s alpha 
coefficients for each construct were: (a) instructional design = .89, (b) instructional practice = 
.90, (c) student-centered teaching = .86, (d) teacher professionalism = .84, and (e) reflective and 
autonomous practitioner = .86. 

Table 1 
 
Cronbach’s Alpha, KMO Measure of Sampling Adequacy, and Bartlett’s Test of Sphericity for 
Factors of the Weekly Self Evaluation 

Factor Cronbach’s 
Alpha 

KMO Measure of 
Sampling Adequacy 

Bartlett’s Test of Sphericity 
Approx. Chi-Square df p-value 

1 .89 .85 2378.96 10 .00 
2 .90 .90 2678.35 15 .00 
3 .86 .79 1524.90 6 .00 
4 .84 .82 1928.87 10 .00 
5 .86 .84 1918.16 10 .00 

Note. 1 = instructional design; 2 = instructional practice; 3 = student-centered teaching; 4 = 
teacher professionalism; 5 = reflective and autonomous practitioner.  
 
Objective 2: Determine if items cluster into latent constructs  
Based on Kaiser's (1970) criteria, factor loadings with eigenvalues of one or more should be 
retained. All factors produced eigenvalues greater than one, and the total common variance 
explained, are listed in Table 2. The communalities of a factor are measures of the proportion 
of common variance (Field, 2018). The factor loadings were strong, and the mean values of the 
factors’ commonalities are as follows: (a) instructional design (M = .62), (b) instructional 
practice (M = .60), (c) student-centered teaching (M = .61), (d) teacher professionalism (M = 
.56), (e) reflective and autonomous practitioner (M = .56). 

 
 
 
 
 
 



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Table 2  
 
Eigenvalues, Percent of Variance, Factor Loadings, and Communalities for Factors of the Weekly 
Self Evaluation   
Factor 1: Instructional Design (Eigenvalue: 3.11; % Variance: 62.22) Factor Loading  Communalities 
Designs instruction for students to achieve mastery  .80 .64 
Selects appropriate formative assessments to monitor learning  .82 .67 
Uses diagnostic student data to plan lessons  .65 .42 
Sequences lessons and concepts to ensure coherence and required 

prior knowledge  
.88 .77 

Aligns instruction with state-adopted standards at the appropriate 
level of rigor  

.79 .62 

Factor 2: Instructional Practice (Eigenvalue: 3.58; % Variance: 59.59) 
Organizes, allocates, and manages the resources of time, space, and 

attention  .82 .68 

Establishes and maintains rapport with students  .76 .58 
Communicates challenging learning expectations to each student  .76 .58 
Establishes and maintains consistent standards of classroom behavior  .75 .56 
Makes the physical environment as safe and conducive as possible  .72 .52 
Uses instructional time effectively  .81 .66 
Factor 3: Student-Centered Teaching (Eigenvalue:2.44; % Variance: 60.92) 
Makes learning goals and instructional procedures clear to students  .80 .64 
Makes content comprehensible to students  .73 .53 
Encourages students to extend their thinking  .78 .61 
Monitors students’ understanding through a variety of means, 

providing feedback to students to assist learning, and adjusting 
learning activities as the situation demands   

.81 .66 

Factor 4: Teacher Professionalism (Eigenvalue: 2.77; % Variance: 55.38) 
Builds professional relationships with colleagues to share teaching 

insights to coordinate learning activities for students   
.71 .51 

Communicates with parents or guardians about student learning  .54 .30 
Is punctual, uses mature judgement, provides accurate reports and 

records (professional responsibility)   
.87 .76 

Presents a professional appearance in dress, grooming, attitude, and 
demeanor   

.80 .64 

Professional behavior is consistent with the Code of Ethics & Principles 
of Professional Conduct of the Education Professionals in Florida  

.76 .57 

Factor 5: Reflective and Autonomous Practitioner (Eigenvalue:2.83; % Variance: 56.50) 
Reflects on the extent to which learning goals were met  .65 .42 
Demonstrates a sense of efficacy   .76 .58 
Demonstrates enthusiasm for teaching  .71 .51 
Demonstrates responsiveness to supervision (ability to accept 

constructive criticism and incorporate suggestions into teaching 
performance)  

.82 .67 

Demonstrates initiative and self-reliance   .80 .64 



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Objective 3: Describe preservice teachers’ performance scores over the 14-week student 
teaching experience 
To describe preservice teachers' performance scores over the 14-week student teaching 
experience, means and standard deviations for each construct are reported in Table 3. For 
instructional design, the three weeks with the highest mean scores were week 14, week 13, and 
week 12. The weeks with the two lowest mean scores were week two and week three. 
Regarding instructional practice, the two weeks with the highest means were week 14, and 
week 13. The two weeks with the lowest mean scores were week two and week three.  

Table 3  
 
Construct Means and Standard Deviations over the 14-Week Student Teaching Experience  

Week  
ID IP SC TP RA 

M SD M SD M SD M SD M SD 
One  2.57 .52 2.57 .52 2.44 .54 2.79 .52 2.73 .51 
Two  2.43 .52 2.47 .50 2.49 .56 2.71 .53 2.73 .53 
Three  2.46 .53 2.56 .51 2.52 .60 2.81 .54 2.77 .57 
Four  2.54 .47 2.62 .50 2.60 .47 2.93 .51 2.96 .50 
Five  2.49 .47 2.76 .53 2.66 .51 2.95 .51 3.00 .50 
Six  2.70 .52 2.75 .46 2.75 .51 3.00 .48 2.97 .50 
Seven  2.69 .57 2.86 .53 2.75 .58 3.02 .53 3.10 .48 
Eight  2.82 .51 2.96 .49 2.85 .53 3.13 .49 3.15 .44 
Nine  2.81 .45 2.95 .46 2.93 .43 3.22 .47 3.21 .45 
Ten  2.85 .51 3.01 .50 3.00 .50 3.19 .53 3.19 .50 
Eleven  2.94 .49 3.05 .51 3.01 .55 3.21 .50 3.19 .47 
Twelve  3.03 .51 3.09 .53 3.08 .51 3.23 .50 3.32 .44 
Thirteen  3.03 .55 3.19 .49 3.10 .53 3.37 .47 3.35 .44 
Fourteen  3.07 .56 3.22 .53 3.14 .59 3.33 .49 3.35 .48 
Note. ID = instructional design; IP = instructional practice; SC = student-centered teaching; TP = 
teacher professionalism; RA = reflective and autonomous practitioner.  
 
As for student-centered teaching, the three weeks with the highest means were week 14, week 
13, and week 12. Week one, week two, and week three had the lowest mean scores. 
Concerning teacher professionalism, week 13 and week 14 were the two highest means. The 
weeks with the lowest two means were week two and week one. For the construct of reflective 
and autonomous practitioner, the three weeks with the highest means were week 14, week 13, 
and week 12. The two lowest mean scores were in week one and week two. There was an 
upward trend with the mean scores over the 14-week placement across each construct. The 
week one scores ranged from 2.44 to 2.79, and the week 14 scores ranged from 3.07 to 3.35. 
Two constructs, teacher professionalism and student-centered teaching, had consistently 
higher scores across the 14 weeks than the other constructs. This data was also formatted into 
a line graph, as seen in Figure 1. 

 



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Figure 1 
 
Preservice Teacher Mean Evaluation Scores by Construct over the 14-Week Student Teaching 
Experience 

 
 

The self-evaluation scores of all five constructs show an upward trend over the 14-week 
student teaching internship, with peaks and valleys scattered throughout. The constructs of 
reflective and autonomous practitioner and teacher professionalism produced higher scores 
than the other three constructs for each week of the student teaching experience. Student-
centered teaching is the only construct which had consistent growth over the 14 weeks, with no 
decline in the mean between any two weeks.  

Conclusions, Discussion, and Recommendations 
 
Student teaching helps with the development of interns in ways that cannot be simulated in a 
university educational environment. Time in real classroom setting allows preservice teachers 
to gain experience interacting with students, parents, fellow teachers, and administration 
(Miller & Wilson, 2010). The required work during a student teach internship encourages 
preservice teachers to follow the cyclical process between the forethought, performance, and 
self-reflection phases of the self-regulated learning process (Zimmerman, 2002). Encouraging 
preservice teachers to practice being self-regulated learners provides the best possible 
simulation of the educational field where teachers must prepare for classes and plan teaching 
strategies, teach content, and reflect on their own teaching performance.  

All five constructs were internally consistent, exceeding the ideal alpha coefficient. The 
instrument was found to be reliable because all five proposed factors met the criteria to be 

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classified as constructs including eigenvalues, total common variance, and factor loading. The 
self-evaluation scores of all five constructs in this study show an upward trend over the 14-
week student teaching internship. The constructs of reflective and autonomous practitioner and 
teacher professionalism produced scores that were consistently higher than the other three 
constructs over the 14-week internship, aligning with the results of previous research (Coleman 
et al., 2021). Researchers should continue to explore this phenomenon to better determine 
how university teacher education programs can emphasize the three lower-scoring constructs. 
Specifically, understanding why the teacher professionalism and reflective and autonomous 
practitioner constructs are higher than other constructs can help emphasize the importance of 
consistent growth in all construct areas. 

The goal of this continued research is to determine why there are peaks and valleys in the 
weekly data based on the information pulled from the journal reflections. The study, thus far, 
has focused on the “performance” phase of self-regulated learning. The researchers hope to 
further analyze the preservice teachers’ participation in the self-regulated learning cycle by 
evaluating their weekly reflections alongside the weekly self-evaluation instrument. It is 
recommended that future research should compare preservice teachers’ mean self-evaluation 
scores to cooperating teachers’ or university supervisors’ evaluation scores as well, to evaluate 
the perceived growth of the student teacher across all parties. The study could be expanded by 
including participants from more recent student teaching cohorts, and other universities or 
states. Additionally, to help reduce any limitations from our sample size, we also recommend 
other institutions utilize this instrument and share their data. While this instrument was found 
to be reliable, we understand that increasing the sample size will only help strengthen the 
results.  

The upward trend of self-evaluation scores leads researchers to see potential for another study 
regarding preservice teachers’ use of the self-regulated learning process throughout the 
teacher preparation program. Researchers can explore how preservice teachers move through 
the three phases of self-regulated learning throughout their college classes, student teaching 
internship, and early years of their career. Better understanding how preservice teachers use 
the self-regulated learning process to help prepare themselves for a career in education could 
help university faculty continue to improve teacher preparation programs. 

University teacher education programs should continue to use the self-evaluation instrument as 
a way for preservice teachers to engage in self-regulated learning. This self-evaluation 
instrument provides an essential form of nonformal feedback, which should be provided to 
preservice teachers in addition to formal evaluations (Miller & Wilson, 2010). Self-evaluation 
should be used in conjunction with cooperating teacher and university supervisor performance 
evaluations throughout the student teaching experience. Other teacher preparation programs 
should seek to use the instrument to help assess preservice teachers’ perceived abilities and 
growth before and during the student teaching internship.  

 



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Acknowledgements 
 
This study had no formal funding source, but fees for publication were covered by 
programming funds from the University of Florida Department of Agricultural Education and 
Communication.  

M. Reaves – writing- original draft, formal analysis, conceptualization; B. Coleman – formal 
analysis, conceptualization, writing- review and editing; C. Jagger – conceptualization, 
supervision, funding acquisition, writing- review and editing; J. C. Bunch – conceptualization, 
supervision, writing- review and editing; G. Israel – formal analysis, writing- review and editing. 

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