An analysis of simSchool, an instructional
simulation for preservice teachers, using an
instructional design framework grounded in the
Model-Centered Instructional Theory
Deb Deale
Burlington High School
United States
dfdeale@gmail.com
Introduction
How does an Instructional designer design a valid and effective instructional simulation?
The following paper explores this question by examining the simulation evaluation
literature, followed by an evaluation of an instructional simulation, simSchool. simSchool
is a web-based simulation designed to emulate various students to provide practice for
preservice teachers in instructional planning, assessment and communication activities.
This paper uses a framework to analyze the simulation, according to the simulation’s
instructional goals and design models. The framework for designing a simulation
approach to instruction, based on the Model-Centered Instructional Theory, provides a
detailed model for dissecting the seven functional layers of a simulation. When combined
with user testing, results indicated that simSchool does provide a valid model of a
simulated environment for preservice teachers to practice instructional activities.
Simulations – a Simplified Reality
A model that provides a simplified version of a system or event is commonly known as a
simulation (Reigeluth & Schwartz, 1989; Gibbons, McConkie, Seo, & Wiley, 2009).
Additionally, simulations provide an interactive abstraction of a real life event or scenario
and are based on dynamic relationships between variables that change over time (Akilli,
2007). Providing a way of manipulating some part of the system supports a deeper
understanding of that system (Gibson D. , 2012). Stripping away irrelevant details allows
the learner to focus on the significant elements of that event or system (Aldrich, 2002).
Gibbons, McConkie, Seo, and Wiley (2009) define an instructional simulation as a
dynamic model of a system that engages the learner in interactions with the model,
causing state changes that are non-linear, in the quest of an instructional goal while
providing instructional augmentations for the learner.
The Framework
The framework utilized in the simulation being evaluated in this paper consists of seven
principles of function: content, strategy, control, messaging, representation, media-logic
and data management (Gibbons, McConkie, Seo, & Wiley, 2009). The framework is
based on Andrew Gibbons’ Model-Centered Instructional Theory. Model-Centered
Instructional Theory focuses the attention of the designer on direct experiences; the
relationship between the learner and the environment, which can be real or modeled
(Gibbons, 2001). This theory assumes that one cannot instruct learners in everything
they need to know therefore instructional products should be designed to support learning
within a particular domain but also enable learners to perform self-instruction (Gibbons,
2001). This is a shift in design thinking, whereas in the past designers have often focused
on creating subject matter products (Gibbons, 2001). Therefore to use this instructional
theory for design, a designer must learn a different systematic design process. This
process includes learning a different set of constructs, order of design and design tools.
Simulations in Teacher Education
Teaching is a very complex work that requires multifaceted decision making to find a
balance between pedagogy and content in an ever-changing context (Christensen,
Knezek, & Tyler-Wood, 2011). New teachers are often overwhelmed by these decisionmaking challenges, challenges that are compounded when specific tools and student
needs are added (Christensen, Knezek, & Tyler-Wood, 2011). Too many new teachers
enter the profession ill-equipped to handle the rigors and demands of managing both
sound pedagogical practices and classroom management strategies vital to successful
teaching (Zibit & Gibson, 2005; Christensen, Knezek, & Tyler-Wood, 2011; Knezek &
Christensen, 2009; Hixon & So, 2009).
Foundational to teacher education, practicum experiences provide an opportunity for
students to learn by doing (Hixon & So, 2009). These experiences often provide for
practice of pedagogical, and content area decision-making skills under the guidance of an
experienced role-model. Many of these experiences consist of live classroom interactions
and observations. These practice opportunities bring with them many obstacles; lack of
time and resources and the ethics of practicing on real-live students (Ferry & Kervin,
2007). These obstacles are often not overcome and therefore reduce the abundance of
practicum experiences, resulting in a decreased capacity for resilience in beginning
teachers. Christensen, et al (2005) contend that increasing this capacity could improve
teacher retention rates.
Many universities have set out to find solutions to the above challenges in teacher
preparation; working independently, several universities are using simulations as a
potential solution.
Purpose Statement
The purpose of this paper was to present an instructional design model for a simulation
(simSchool) in order to determine the potential effectiveness of a simulation. Efforts to
do this help to contribute to the knowledge base for instructional simulation design.
Using the framework described previously, connections were made between choices the
developer made in their efforts to provide an effective solution to the instructional goal.
The guiding framework provided a method for determining if the instructional simulation
was an effective instructional solution for the desired learning goals.
simSchool
SimSchool is a web-based procedural simulation designed and developed to offer practice
experiences for preservice teachers (Knezek & Christensen, 2009; Gibson D. , 2009).
This simulation dynamically models learner behaviors in an effort to provide practice
opportunities for teaching. Inspired by the increase of use and value for simulatedlearning, the developers sought to provide a method for better teacher-preparation
(Christensen, Knezek, & Tyler-Wood, 2011). simSchool uses the “approach based on the
factor-analytical model” comprised of theories of cognition, personality and
communication (Gibson D. , 2011; Gibson & Knezek, 2011).
These solutions match with the above rationale for using a simulated learning approach to
instruction. Providing transfer of learning by teaching complex tasks in an environment
that approximates a real world setting in particular ways is an effective and efficient
approach to instruction and a highly motivational strategy (Reigeluth & Schwartz, 1989).
Investigations of simSchool with a many universities are on going, including incentives
from the WAVE I Grant from Next Generation Learning Challenge. At the time of this
writing, the simSchool.org site reported 101 institutions in 137 countries makeup a
worldwide network of users. Many of these users are undertaking research initiatives that
will contribute to a publication by Association for Advancement in Computing in
Education (AACE) and Society for Information Technology and Teacher Education
(SITE). These undertakings provide accessibility to information regarding the analysis,
design, development, implementation and evaluations of simSchool as well as unlimited
access to the product. The wide-spread use of this simulation also lends credence to its
relevance as a legitimate product.
Project SETS, a project funded by the National Science Foundation, was an effort to
measure the validity of the simStudents by comparing students in simSchool with
students in a real school setting (Christensen, Knezek, & Tyler-Wood, 2011). The
simulated students were constructed based on real teacher ratings of five real student’s
characteristics. The same “life in a pond” content and activities were instructed in both
the real classroom and the simulated classroom. Although much data was gathered and
compared, for the purposes of this paper it can be reported that findings indicated that
real student was “moderately well” modeled by the simulated student (Christensen,
Knezek, & Tyler-Wood, 2011).
Given these initial findings, it can be concluded that simSchool shows promise in
providing a solution to the instructional problem of lack of complex decision-making
skills for young teachers.
Methods
An analysis of simSchool was conducted using a practice of reverse engineering and user
testing. Modeled after Andrew Gibbons’ (2000) method of breaking down and
identification of multiple components within an instructional simulation. This process
began with an exploration of simSchool, followed by dissecting the simulation according
to Gibbon’s framework. User testing, although not specified by the chosen framework,
provided a means to determine if the simulation functioned as intended. The users
participated in a self-report pre-survey and post-survey of teacher preparation skills, the
same as those used in the previously reported study of simSchool (Christensen, Knezek,
& Tyler-Wood, 2011). The results were used to determine if the simulation was an
effective means of reaching the intended learning goals.
Participants
The participants were made up of thirteen undergraduate education majors, eleven
females and two males between the ages of 18 – 22 and one over the age of 55, from a
Teaching with Technology class from a southeastern university during the Spring 2012
semester.
Procedures
The participants each had three sessions of simulations with a classroom of the same
three simulated students within a predetermined subject area of technology. It was hoped
that by using the same simulated classroom of one to three students, the participants
would have the opportunity to evaluate their effectiveness using the reports and teaching
effectiveness graph that is produced at the end of each session. Each ‘teaching’ session
lasted 10 minutes and was assigned on three separate days. Prior to starting, the
participants registered with the site and completed a survey of teacher preparation skills.
The first session consisted of a short instruction on using the simulation and some
independent exploration. The second and third sessions were completed during a lab time
with the survey of teacher preparation skills administered immediately following the
simulation session. Observations were conducted and participants were questioned
regarding their attitudes and perceptions of the functionality and interest of the
simulation.
Instruments
A Teacher Preparation Survey (TPS) was adapted from Eric Riedel’s (2000) Teacher
Beliefs and Preparation Survey. The Teacher Preparation Survey provides a way for the
preservice teacher to rate their perceived confidence and experience related to eight
different topics: knowledge of students, pre-planning instruction, making and using tasks,
making and using assessments, re-planning instruction, classroom decision making,
making and using a post-assessment, and reflection on teaching. These were rated on a
five point Likert scale from Very Low to Very High. Administering this survey before and
after the simulation activities provided a method for determining if there was a difference
in perceived skill level.
Results
User Testing
A comparison of the data from the pre and post self-report survey indicated an increase in
the preservice teachers’ perceptions of their preparation after using the simulation (Table
1).
Table 1
Confidence
Level
# of
Participants
Mean – SD –
# Of
Pre
Pre
Participants
Survey* Survey*
Mean –
Post
Survey*
SD –
Post
Survey*
Knowledge of
Students
14
1.07
0.26
12
2.5
0.79
Pre-planning
Instruction
14
1
0
12
2.93
0.9
Making &
Using Tasks
14
1
0
12
2.83
0.93
Making &
Using
Assessments
14
1
0
11
2.55
0.93
Re-planning
Instruction
14
1
0
11
2.91
0.94
Classroom
DecisionMaking
14
1.07
0.26
12
3.17
1.26
Making &
Using a PostAssessment
14
1
0
11
2.55
0.93
Reflections on
Teaching
14
1.07
0.26
11
2.91
1.04
* Likert Scale of 1=Very Low, 2=Moderately Low, 3=Medium, 4=Moderately High,
5=Very High
Discussion and Conclusion
The purpose of this paper was twofold: determine the potential effectiveness of
simSchool, and to increase the ability to communicate designs in deeper detail and to
achieve more complex designs.
This paper began with a brief definition of instructional simulations and their potential as
instructional solutions. Concentrating on a particular simulation sharpened the focus to a
particular instructional problem: Too many new teachers enter the profession ill-equipped
to handle the rigors and demands of managing both sound pedagogical practices and
classroom management strategies vital to successful teaching (Zibit & Gibson, 2005;
Christensen, Knezek, & Tyler-Wood, 2011; Knezek & Christensen, 2009; Hixon & So,
2009). It was cited as difficult to truly determine the validity of simSchool by measuring
an increase in resilience of new teachers, rather it was argued that preservice teacher’s
perceptions of a change in their confidence and knowledge within particular skills of
teaching could indicate a potential for increased resilience. The results from the chosen
survey (TPS) did indicate an increase in both confidence and knowledge of particular
skills important to teaching. The data from the Teacher Preparation Survey, though
limited in validity due to small user testing participation, also supports previous research
findings of simSchool. The results indicate the success of the simulation in meeting its
instructional goal of increasing the capacity of managing the demands of a teacher thus
potentially increasing the resilience of new teachers. This concurs with other research on
the validity of simSchool as an indication of its success in matching the instructional
goal.
The chosen framework combined with user testing made it possible to make connections
between choices the developer made in their efforts to provide an effective solution to the
instructional goal. It provided another method for determining if the instructional
simulation was an effective instructional solution for the desired learning goals. The
methodology of employing the framework proved to be helpful as it provided a means of
identifying the functional intents of each layer and connections to the other layers. As
detailed above, simSchool is a very complex procedural simulation that functioned as it
intended. simSchool carefully and systematically provides a realistic environment for
preservice teachers to practice the complex decision-making skills needed to balance
pedagogy and content in an ever-changing context.
Some augmentations are present within the simulation, but simSchool’s primary role is to
provide a realistic environment for practice. It is quite clear from the hosting website and
the developer that simSchool is designed for use within a preservice teacher education
program under the guidance of an instructor. As is outlined on the opening home page of
simSchool.org; its use is as a component to teacher education. A tremendous amount of
material and resources are available at the simSchool.org site for an instructor of
preservice teachers, as well as live webinars on variety of topics. These resources do
provide external augmentations for both an instructor and a learner. It was argued that
good instructional simulations are grounded in common design principles, and that
simSchool was no exception. The principles were easily identifiable within this
simulation, which provides additional evidence to its effectiveness.
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