SW Practice I
SW Practice I
Global Com Bsd Resch
Global Com Bsd Resch
- American Board of Professional Psychology. 01/2002 - present. Position : Diplomate in Counseling Psychology.
- American Board of Professional Neuropsychology. 01/2002 - present. Position : Diplomate in Clinical Neuropsychology.
- Associate Professor of Social Work and Psychology [Tenured] (1999-2009)- Brigham Young University, Provo, Utah. Taught clinical and research courses as part of a full-time, tenured position within a nationally accredited (CSWE) School of Social Work. Had Graduate Faculty Status (GFS). 09/1999 - present .
- Clinical Pediatric Neuropsychologist, (1995- 1999). Utah State Hospital, Provo, Utah. Established and maintained neuropsychological laboratory. Provided psychological and neuropsychological assessments of adults, adolescents, and children. Designed cognitive rehabilitation treatment plans for patients with brain dysfunction. Supervision of doctoral interns in psychology and neuropsychology. Conducted ongoing neuropsychological and rehabilitative research. Established the pediatric neuropsychology lab, including developing a computerized testing, scoring, charting system, and database. Maintained ongoing review of testing materials for children. Established a cognitive rehabilitation program using the process-specific approach as well as biofeedback, and psycho-physiological assessments. 09/1995 - present .
My overarching teaching and learning goals as a research and statistics teacher is to develop, within the students, the research and statistical knowledge and skills that they will need as to effectively and competently work within social work agencies as professionals. I recognize, however, that many students who choose social work as a profession often have the bias view that they are “impaired” when it comes to understanding and correctly using mathematical based skills. Students entering my class have repeatedly told me: “I hate math because I just don’t get it.” “There must be something wrong with my brain.” “Can’t I just hire someone to do this stuff once I am a social worker out in the field.” In other words, they are convinced that they are unable to perform the research analysis and interpretation skills required to be a competent social worker. Consequently, the typical goal of the students who strongly hold these beliefs is to simply pass the class “somehow,” and then meekly become the best social worker that they can without these skills.
It is my professional belief as a social work educator, however, that all of my students are becoming social work professionals; therefore, they must master all of the skill sets expected of those providing professional level services. If they were in medical school, they would not be allowed to claim an inability to learn a set of skills because of poor aptitude, lack of interest, or learning disabilities. It would be unimaginable for a medical school graduate to state, “I just didn’t get anatomy. My mind does not work that way. I am great at direct patient care, but don’t ask me the names of any body parts. I just didn’t do well in that class!” In similar fashion, it is my passionate belief that every BSW level social work student should obtain a high level of competence in every class and subject. As a statistics and research teacher, I expect that each student will learn the professional level of competence in research and statistics that is necessary for them to become a competent social work professional. In other words, I expect them to learn all the skills sufficiently in my class so that you may use all of them in their practice competently.
My response as a teacher to their dysfunctional beliefs has been influenced by my early clinical experience. After I earned a MSW, I worked for 12 years at the Utah State Hospital. For several years, it was my responsibility to work with profoundly learning-disabled and mentally ill children who were falling behind in school by several grade levels. Many had neurological deficits. In an effort to better serve these children, I eventually earned a Ph.D. in Counseling Psychology, followed by a 2-years post-doctoral training program in Neuropsychology. Consequently, I have the background, training, and experience necessary to effectively assist extremely impaired people to learn. In brief, I am not impressed by the argument of students that they too impaired to learn the skills taught in my class, in view of the fact that they all have already gained admission to the University of Utah [which is ranked as the 82nd best university in the world by the Academic Ranking of World Universities (ARWU); see ]. In other words, I have successfully helped a significant number of people with profound impairments to overcome their difficulties and learn. Therefore, I have no hesitation in stating that regardless of a student’s past experience with math or statistics, that they can be fully successful in my class and learn the foundational skills that are taught.
The teaching method that I use is known as “Mastery Learning.” This approach is based upon Benjamin Bloom's “Learning for Mastery Model” (Bloom et al., 1956). He demonstrated that the average student taught using mastery learning methods passed at the 95th percentile of traditionally-taught classes. Subsequent refinements to Mastery Learning methods by Robert Block (1974) has led to the assertion that “virtually all children” can master a subject using this approach. In other words, Mastery Learning is an instructional method that “presumes all students can learn if they are provided with the appropriate learning conditions.” According to educators who use the Mastery Learning approach, if a student fails to learn, the fault lies with the instructional methods used, and not due to the student’s lack of ability. The educational challenge is to provide enough time and use appropriate instructional strategies so that all students can achieve the same high-level of learning (Bloom, 1981).
The vital elements of Mastery Learning are:
Clearly specifying what is to be learned and how it will be evaluated;
1. Allowing students to learn at their own pace;
2. Assessing student progress and also providing appropriate feedback or remediation (Ibid).
Teaching Element One: Clearly Specify What is to Be Learned. At the beginning of each topic section, I will begin with a lecture introducing a selected clinical topic and then giving the student an investigative case example to consider and discuss. For instance, I may begin a topic area by examining trauma among Iraqi war veterans. Through discussion, a group of clinical questions will be developed regarding the investigative cases, which the student will likely need to answer as they work in agency settings. For example, the question may be asked, “Do female veterans exhibit the same symptoms of PTSD as do the male veterans?” Lecture, demonstration, and discussion will be used to introduce the statistical methods and data analysis techniques that the student is expected learn. Specifically, I will use lecture and discussion to provide the student with a conceptual understanding of a given statistical technique, as well as the decision-making process that identifies the appropriateness of choosing that technique. I will then demonstrate to the student how to conduct the analysis within SPSS. Next, I will demonstrate to the student how to identify and interpret the answer to the clinical questions from the printout that is generated. Finally, I will demonstrate to the student how to communicate these findings clearly within the professional literature.
Teaching Element Two: Allow Students to Learn At Their Own Pace. Following the lecture, demonstration, and discussion, during the last 45 minutes of class, the students will work individually on homework questions that will allow them to review, practice and apply the new professional skills and knowledge that they were just taught. The homework will be structured as self-learning modules that will re-teach and reinforce the concepts and skills immediately after they are taught. Students will be expected to correctly identify and calculate key statistical informational components needed to choose the correct statistical analysis. The students will then use SPSS to conduct the appropriate analysis and correctly interpret the results. Students will rework their analysis of the data, then revise and resubmit their answers to the homework until complete mastery of the topic area is demonstrated by achieving a perfect score (100%) on the homework. Students are not allowed to advanced to a subsequent learning objective until they demonstrate mastery with the current one. In other words, subsequent homework assignments will not be made available to the student until they complete the current homework assignment.
Teaching Element Three: Assessing Progress and Provide Immediate Feedback and Remediation. In Mastery Learning, it is critical that students receive frequent and specific feedback by using diagnostic, formative tests; as well as regularly correcting mistakes students make along their learning path. Along with being structured learning modules, the individual homework assignments are designed to provide both assessment and immediate corrective feedback. Specifically, homework is contained in WebCT. After the lecture and demonstrations, students are given the opportunity to directly apply your new knowledge with similar problems to those that were just presented. As they complete each section, the computer will identify any difficulties that they may have had with the homework, and then give them immediate feedback regarding the proper method to complete the problem. If they continue to have difficulty, there are video files that will give additional explanations. Additionally, the last 30 to 45-minutes of class are devoted to allowing them to complete your homework and to ask me questions immediately. If they continue to have difficulties, they may arrange to receive personal tutoring to learn concepts. They are to continue to resubmit homework until you achieve a 100% grade. At that point, WebCT will make the next homework assignment available to them. All homework must be completed at the 100% level in order for the student to qualify to take the midterm and final exams. If by the end of the course they have not completed their homework (so that they are qualified to take the exam) they may choose to take either an “Incomplete” or “Failed” grade for the course; and they will be expected to retake the course from the beginning.
Additional Teaching Element: Final Assessment. The mid-term and final exams are used to document if the course learning objectives have been achieved and if the student has achieved mastery of the curriculum.
Assessment of Teaching. I have taught five classes, four of which I have received student feedback. Predominantly, the feedback from the students is positive. My ratings are in the 5's (in a six-point scale), and the written comments typically express strong support of my teaching approach. These ratings and feedback are consistent with the feedback I have received over my 18-years of teaching.
The feedback from one class, however, concerned me. Specifically, the feedback that I received for SW 7722 was disturbingly negative. This was a small class of five doctoral students that I team taught with another professor (who had taught the class for several years). Specifically, I was responsible for two lectures out of the fifteen lectures. Only one student gave written feedback, and she was clearly disgruntled. Given the low number of students, and the outlying nature and personal focus of the feedback, the accuracy of the feedback of the class is suspect. Nevertheless, I will continue to monitor my student evaluations to ensure that my performance as a teacher remains strong.
Advance Social Work Statistics
This class prepares the student to setup, maintain, and use agency-based databases. Specifically, the student will learn how to analyze data to answer questions about clients to make clinical decisions; to provide outcome information to obtain funding; and to answer hypotheses to improve treatment.
Statistics II: Multivariate Analysis
This second course in the year-long statistics sequence provides students with theoretical and practical understanding of the logic and application of selected statistical advanced multivariate statistical procedures. Students will learn how to choose the most appropriate multivariate procedures for detecting important differences and predictors using multiple regression, logistic regression, factor analysis, multivariate analysis of variance and repeated measures analysis of variance. The course uses the SPSS for Windows computerized statistical package for data processing and analysis.