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AAQEP Accreditation 2022

Standard 1 Aspect B

Standard 1b: Evidence shows that, by the time of program completion, candidates exhibit knowledge, skills, and abilities of professional educators appropriate to their target credential or degree, including: Learners; learning theory, including social, emotional, and academic dimensions; and application of learning theory


Data Sources & Analysis

Data Source 1

CI 161 Micro-Teaching Presentation Project

Description of Data Source:
In CI 161: Methods and Materials in Agricultural Education, the CI 161 Micro-Teaching Presentation Project requires candidates to plan and deliver a microteaching lesson to their peers. This assignment takes place during the semester prior to or during their initial student teaching. The instructor assigns a grade based on the CI 161 Teaching Evaluation Rubric for each presentation following a critique by the class and the instructor. The instructor uses this rubric to evaluate students’ lesson plans and teaching presentations. The instructor also requires students to complete this assessment online for each of their peers’ presentations. Peer evaluations are reviewed by the instructor and used for participation/attendance purposes but are not a part of the students presentation grade.

Perspective Captured from Data Source: Faculty

Rationale for using Data Source:
In order to successful deliver their microteaching lesson, candidates have to draw on their knowledge of learners and apply that learning in their instruction.

Specific Elements of Data Source:
Overall scores on the rubric are used to evaluate candidates' success. 

Definition of Success for Each Element:
The instructor’s expectation is that all students will score a “B” (80%) grade or better on this assignment, although a “C” (70%) grade is accepted as meeting the learning outcome. Our overall program goal is for all candidates to meet this learning outcome with a “B” (80%) grade or higher. The total points possible for this assignment is 150, so an overall mean score of 120 points or better is our goal.

Displays of Analyzed Data:
Figure 1: Mean Scores for CI 161 Micro Teaching PresentationsCI 161 Micro Teaching Presentation

Link to Full Dataset: CI 161 Teaching & Curr Project Data

Interpretation of Data:
Over the period of Fall 2015-2019, students’ mean scores for the Micro-Teaching Presentations have ranged from 127.4 (2016) to 137.0 (2019). Data from 2020 was not included since the CI 161 course was delivered online due to COVID restrictions which created new challenges for students not comparable with those in previous years. Data collection will resume in Fall 2021, the next time the course is offered.

The past two years showed a notable increase in student scores. In all four years students have met the overall program goal of scoring at least 80% (B grade) or higher on the Micro-Teaching Presentation. As we reflect on the rise in scores in 2018 and 2019, we do not have an obvious reason for the increase. One reason may be the increase in the number of candidates within each cohort, which may help to level out scores. However, this is something we will look into further after Fall 2021, the next time data will be collected and analyzed from the micro-teaching presentations.

Data Source 2

Professional Competencies -- Observing and Teaching Agriculture Classes

Description of Data Source:
The Observing and Teaching Agriculture Classes competency requires candidates to obtain copies of course of study and teaching plans used by their mentor teacher during their first semester in their field placement (EHD 155A: Initial Student Teaching). They are to observe agriculture science and agricultural mechanics classes, observe class management methods including discipline, and take notes during observations and discuss with the mentor teacher. Candidates are also required to develop lesson plans for assigned classes and teach units of instruction as agreed upon with the mentor teacher.

Perspective Captured from Data Source: Mentor Teacher

Rationale for using Data Source: 
As they observe and teach agriculture classes, candidates further develop their knowledge of learners and how to engage learners in the agriculture content. When they begin to teach classes, they are able to apply what they have learned, further refining their knowledge.

Specific Elements of Data Source: 
Two Professional Competencies:

  • Discovering Community and Student Needs in Developing Ag Ed Programs 
  • Guiding, Counseling, Selecting, and Placing Pupils 

Definition of Success for Each Element:
Candidates are asked to complete as many of the competencies as they can. The expectation is that candidates will complete all competencies. Some candidates may not complete all the items due to various circumstances. Mentor teachers provide university coaches with feedback on each candidate’s performance in regard to meeting expectations for professional competencies.

Displays of Analyzed Data: 

Table 1: Mean Scores by Semester for Seven Observing and Teaching Professional Competencies

Data
Professional Competencies Fall 2019
N = 13
Spring 2020
N = 15
Fall 2020
N = 21
Spring 2021
N = 10
Getting Established in the School 10.92 10.38 10.92 10.90
Discovering Community and Student Needs in Developing Ag Ed Programs 6.92 5.75 6.84 6.80
Observing and Teaching Agriculture Classes 6.92 6.93 6.96 7.00
Out-of-Class Instruction and Supervision 2.00 1.94 2.00 2.00
Guiding, Counseling, Selecting, and Placing Pupils 3.00 2.25 3.00 3.00
Organizing, Administering, and Maintaining a Department 11.00 10.44 10.69 10.60

Link to Full Dataset: EHD 155A Professional Competencies

Interpretation of Data:
The EHD 155A Competency Checklist includes seven Discovering Community and Student Needs in Developing Ag Ed Programs and three Guiding, Counseling, Selecting, and Placing Pupils competencies that candidates are to accomplish. On the checklist, candidates indicate the date they accomplish a competency and the mentor teachers write their initial by the date to verify it has been accomplished. Over the four semesters, three candidates completed six of the seven Discovering Community and Student Needs in Developing Ag Ed Programs and the other 56 candidates completed all seven competencies to create the average scores reported in Table 1. For  Guiding, Counseling, Selecting, and Placing Pupils 44 candidates completed all three competencies while six candidates were unable to complete all three competencies.

Data Source 3

Fresno Assessment of Student Teachers (FAST) Teaching Sample Project (TSP)
The Teaching Sample Project of the Fresno Assessment of Student Teachers, the performance-based assessment all candidates are required to pass, is scored using specific rubrics. There is a rubric for each of the seven sections of the teaching sample project. The agriculture university coaches have all been calibrated to score the teaching sample project. 

Perspective Captured from Data Source: University Coach

Rationale for using Data Source:
In this section of the TSP, candidates are to describe two
different times while teaching the unit when they adjusted their original design based on student learning. They are to describe how they were monitoring students, describe how students performed differently than expected, what was changed, and why candidates thought the change improved student learning. The instructional decision making section of the TSP requires candidates to show evidence of monitoring students during instruction and make adjustments to address student needs. Adjustments are to be aligned with learning outcomes. 

Specific Elements of Data Source:
Teaching Sample Project Instructional Decision Making Rubric  
Total score for three areas: 

  • Monitoring Student Learning
  • Adjustments Based on Knowledge of Student Learning and Providing Access to Curriculum
  • Alignment Between Adjustments and Learning Outcomes

Definition of Success for Each Element:
Although the agriculture university coaches encourage candidates to strive for a score of four on the scoring rubric, the coaches would like to see average scores of 2.5 or better. Candidates must score a two or better on the scoring rubric to show they met the expectation for the instructional decision making section of the project.

One reason scores are not higher may be that the agriculture coaches tend to be conservative in their approach to scoring. They are most concerned about students failing to score a 2 and not concerned as much about students scoring higher. Still, this is something the program may want to look into further to ensure that candidates are developing the necessary knowledge of learners and learning theory and that they understand how to apply this knowledge when planning instruction.

Display of Analyzed Data:

Table 2: FAST Teaching Sample Project (TSP) Students’ Instructional Decision Making

Teaching Sample Project Data Summary Fall 2018 - Spring 2020

Data
Semester Fall 2018
N=11
Spring 2019
N=14
Fall 2019
N=13
Spring 2020
N=15
Students in Context 2.27 2.07 2.27 2.33
Learning Outcomes 2.09 2.04 2.31 2.20
Assessment Plan 2.09 2.07 2.08 2.07
Design for Instruction 2.18 2.07 2.19 2.20
Instructional Decision Making 2.18 2.21 2.31 2.07
Analysis of Student Learning 2.09 2.00 2.19 2.00
Reflection and Self-
Evaluation
2.27 2.11 2.23 2.07

Link to Full Dataset: FAST TSP F18 Sp20 Ag Students Summary and Data

Interpretation of Data: 
Although the candidates average scores did not reach the goal of 2.5 or better, all candidates met the expectation for the instructional decision making by scoring a two or better (a two score is required to pass) using the TSP scoring rubric. One reason for the low scores may be that the agriculture coaches tend to be conservative in their approach to scoring. They are most concerned about students failing to score a 2 and not concerned as much about students scoring higher. Still, this is something the program may want to look into further to ensure that candidates are developing the necessary knowledge of how to apply their knowledge of learners and learning theory when planning instruction.

Next Steps: 
The microteaching presentation assignment will continue to be a key assignment for CI 161 as it provides an introduction to teaching to students that are just entering the credential program and initial student teaching. 

For our professional competencies we will spend more time preparing our candidates to meet the needs of a variety of students and preparing them to guide and counsel their students.

We realize the checklist has limitations in preparing candidates  mastery of these competencies.

The FAST teaching sample project is approved by the California Commission on Teacher Credentialing (CCTC) and will only change when revisions are requested by that agency. Due to increased enrollments, the university coaches supervising the agriculture specialist candidates are often part time lecturers. The program will continue to seek and train university coaches that have prior experience teaching agriculture in secondary school settings. Selection of high quality mentor teachers will continue to be a point of emphasis. To evaluate our efforts in this area, we will continue to analyze the data we collect each year and discuss as program faculty how we might improve the scores of our candidates. Some areas to explore include devoting additional time in the AGRI 280: Seminar in Agricultural Education Seminar to the TSP and incorporating instructional decision making as a topic in our AGED 187: Organization, Administration, and Supervision of Agricultural Education course.

The TSP Instructional Decision Making section requires candidates to describe two examples of their lessons not meeting their expectations and describe what changes or adjustments they made to ensure students were learning. We plan to incorporate instructional decision making in our AGED 187 course to prepare candidates for dealing with problems they encounter in their teaching to determine the causes of problems including type of learners and appropriate learning theories.

Aspect C →