Enhancing Learning Through Individualized Feedback in Large Medical Classes

Introduction

In a classroom environment, feedback acts as a means of identifying and minimizing errors, as well as determining performance and reinforcing learner knowledge. Theoretically, feedback is anchored on the conscious competence theory, which states that learning consists of four stages to be considered successful learning, and that leaner feedback plays a vital role in facilitating the learner to go through the four stages (Howell, 1983). Besides, feedback can be used in combination with self-directed learning to enable the achievement of corrected understanding and conscious competence, all of which make use of feedback. Ideally, without the development of corrected understanding, the learner finds it hard to achieve learning progress.

According to Kolb & Fry (1972), learning occurs in a cycle that begins with the learner's identification of what they know before they can figure out what they need to know. The Cycle continues with the learner’s evaluation of how much they know and how well they understand a concept, which when effectively highlighted, can enable the learner to correct their knowledge through feedback. However, without learner feedback, it is impossible to complete the cycle. Therefore, the proposed study seeks to identify how individualized feedback can be delivered and used in a large class of medical teaching, as part of enabling learners to successfully go through the conscious competence learning model.

Summary Literature Review

Existing literature indicate that various feedback models that can be used to guide the learner through the Kolb & Fry’s (1972) cycle. For instance, in clinical teaching, some of the most implemented models include the Chicago model (Brunkner et al, 1999), ALOBA (Silverman et al, 1996), SCOMPE MODEL (SCOMPE, 1996) and the SET-GO (Chowdhury & Kalu, 2004). These models present an opportunity for teacher-facilitated feedback and can been used based on the teacher’s abilities and preferences. Besides, research has consistently evaluated how feed-forward evaluations can improve learner’s performance within the clinical care settings by focusing on previous performance and internal standards considered best practice (Kluger & Dijk, 2010). However, Molloy (2010) contend that teacher-facilitated models have higher demands for resources, creating a need for alternative feedback models that can enhance the delivery of universal feedback within a large number of learners while incorporating the essential elements of effective feedback.

Research by Race (2005) and Carter (1984) suggest that effective feedback must be non-evaluative, timely, constructive and specific. Therefore, the proposed study will explore how learners will respond to an innovated feedback model that aligns to summative assessment in the teaching of medical science, thereby enabling the delivery of feedback from a large cohort of learners. The proposed feedback model has been featured in the General Medical Council (2011) but has never been clearly explained. Thus, the study will evaluate how the feedback model can be blueprinted to enable large numbers of learners to automatically offer individualized feedback, and how it can be used after learner assessment to automatically create a report indicating how each learner has performed based on the learning models and objectives.

Sampling

The researcher will conduct two different surveys for different purposes. Both the first and second surveys will be administered to a convenient sample of 20 students. Convenience sampling is a non-probability technique of sampling whereby the samples are selected due to their availability and accessibility to the study. The convenient sampling methodology is considered appropriate for the proposed study because it would save on time and costs (Atkinson & Coffey, 2002). The participants will be selected just because they can easily be accessed, rather than selecting a representative of the student population. This technique is preferred for the proposed study because it is inexpensive and fast.

Research Methodology

The study will use a behavior-based survey to collect data from student participants on the effectiveness of the proposed individualized feedback tool. The researcher will target respondents in their first and second year of training, with data collected through SurveyMonkey – an online survey platform. The respondents will be required to self-complete the online behavior-based questionnaire. While the first survey will be behavior-based, there will be the second survey meant to evaluate the student’s attitudes regarding the proposed individualized feedback tool.

Several theoretical underpinnings justify the use of qualitative approaches (i.e, questionnaires and interviews) in the proposed study. First, Apan et al (2012) argue that interviews and questionnaires and interviews are kin to naturalistic enquiries that allow the researcher to explore a phenomenon from the respondent’s perspective. The main aim of the proposed study is to explore the effectiveness of individualized feedback tool in a large class of medical students. Therefore, because the tool is expected to have a positive impact on the student’s attitude and behavior throughout the learning cycle, questionnaires and interviews will be the most effective tools in gauging the respondent’s behavioral response and attitude towards the tool respectively.

Due to the use of surveys and questionnaires as methods of data collection, the study is expected to take an interpretive research paradigm. Ideally, the interpretive research paradigm entails the assessment of a phenomenon from the perception of the people experiencing it (Bloor & Wood, 2006). The main objective of the proposed study is to explore the effectiveness of an individualized feedback tool on the learning outcomes of a large number of students. Therefore, the researcher will be interested in gauging the tool’s impact from the perspective of the students, justifying the use of interpretive research paradigm.

Data Analysis

The proposed study will rely on statistical methods of data analysis to analyze the collected data. This will include measures of central tendency (mean, mode, and median). The analysis of central tendency and distributions will be of great importance because the researcher will need to know how the tool impacted on each portion of the respondents. Furthermore, measures of central tendency will be of great help because the researcher will have an opportunity to evaluate whether the tool impacts the majority or not.

Furthermore, the choice of statistical data analysis methods for the proposed study is informed by the fact that the questionnaires will have a Likert scale. Likert scales are used in questions that ask the respondents to indicate their agreement or satisfaction from strongly agree/satisfied to strongly disagree/dissatisfied. While Likert scales are ideal survey tools (Given, 2008), there is a significant disagreement in the academia regarding how to analyze Likert scale data, with the most contentious issue being whether a researcher should use non-parametric or parametric tests to analyze the data. Nonetheless, in the current study, the researcher will consider using the most convenient among the two; considering data at hand. Specifically, the researcher will use the Likert scale to evaluate the value of individualized feedback tool in nursing education, whereby the scale will range from not useful=1 to very useful=5. The researcher will then use statistical tools to analyze the pattern of answering and central tendency of answers given by the respondents. The statistical significance will be measured agaist a benchmark of p < 0.05, while the Shapiro-Wilks test will be used to determine the parametricity. The researcher is also aware that the study validity may be affected by bias emanating from pattern answering, central tendency and order effect. Therefore, the questionnaires will be designed to avoid these effects. Ultimately, there will be a graphical presentation of data through the use of graphs and pie charts.

Ethical Considerations

Because the proposed study will involve human subjects, the researcher will make several ethical considerations. First, the respondents’ integrity, as well as the interview quality, will be maintained. Next, all the respondents’ identities will be kept held under anonymity. No personal details such as name, the email address will be disclosed. Besides, all the respondents are expected to participate willingly after signing a consent form. While evaluating educational research ethics, Given (2008) emphasized the need for respondents to have the freedom of withdrawing from the study any time they wish. Based on this assertion, the researcher will allow the respondents to withdraw from the study as and when they wish to do so.

Reflective Discussion

Once initiated, the proposed project will take a maximum of 4 months. I believe that four months will be enough to get develop the research proposal, conduct the background research, collect data, analyze and do the final write up. However, the researcher will give a time allowance for any emergency.

Because the study is set to use a qualitative research design, there are several acknowledgeable advantages and limitations of this research design. For instance, the use of surveys and questionnaires will provide an opportunity for me to evaluate the data by concentrating less on the metrics and focusing more on the sensitive information available in that data (Apan et al, 2012). This will enable me to retrieve an enhanced level of detail from the data, useful in making quality conclusions on the subject matter. However, one limitation of the data is that I will have to bear with is the subjectivity of the information and conclusion of the study because what I might derive from the data as important may not be considered by another researcher as pointless. Thus, my perspectives may derail the credibility of the study. However, I will try to be as objective as possible in my analysis.

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References

Atkinson, P. and Coffey, A. Revisiting the Relationship Between ParticipantObservation and Interviewing’, in J.F. Gubrium and J.A. Holstein (ed.) Handbook of Interview Research, pp. 2002;801–14. Thousand Oaks, CA: Sage.

Apan, S. D., Quartaroli, M. T., & Riemer, F. J. Qualitative research: an introduction to methods and designs. San Francisco, Jossey-Bass. 2012.

Bloor, M & Wood, F. (2006) Keywords in Qualitative Methods: A Vocabulary of ResearchConcepts. 2006 London: Sage.

Chowdhury R, Kalu G. Learning to give feedback in medical education. Obstet Gynaecol. 2004;6:243–247. doi: 10.1576/toag.6.4.243.27023.

General Medical Council (GMC) Assessment in undergraduate medical education. London: GMC; 2011. (Advice supplementary to Tomorrow’s Doctors 2009).

Given, L. M. The Sage encyclopedia of qualitative research methods. Los Angeles, Calif, Sage Publications 2008.

Howell WC, Fleishman EA. Human performance and productivity. Vol 2: Information processing and decision making. Erlbaum: Hillsdale New Jersey; 1982.

Kluger A, van Dijk D. Feedback, the various tasks of the doctor, and the feedforward alternative. Med Educ. 2010;44:1166–1174. doi: 10.1111/j.1365-2923.2010.03849.x.

Kolb D, Fry R. In: Toward an applied theory of experiential learning. Cooper CL, editor. London: John Wiley; 1972. (Theories of group processes).

Silverman J, Draper J, Kurtz S. The Calgary-Cambridge approach to communication skills teaching. 1. Agenda-led outcome-based analysis of the consultation. Educ Gen Pract. 1996;7:288–299.

Standing Committee of Postgraduate Medical and Dental Education (SCOPME) Appraising doctors and dentists in training. London: DoH; 1996.

Molloy E. The feedforward mechanism: a way forward in clinical learning? Med Educ. 2010;44:1157–1158. doi: 10.1111/j.1365-2923.2010.03868.x.

Race P. Making learning happen. London: SAGE Publications; 2005.

Van de Ridder M, Stokking K, Mcgaghie W, Cate O. What is feedback in clinical education? Med Educ. 2008;42:189–197. doi: 10.1111/j.1365-2923.2007.02973.x.