The Role of Feedback in Classroom Learning

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 learner 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 progress with respect to their learning.

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. The details of this cycle will be explored in subsequent sections. 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 pass through the conscious competence learning model, which explains the processes that a learner goes through to acquire new skills.

Literature Review

Existing literature indicates 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 be 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) contends that teacher-facilitated models have high 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 innovative feedback model that aligns to summative assessment in the teaching of medical science, thereby enabling the delivery of feedback to a large cohort of learners. The proposed feedback model has been featured by 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 receive 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.

Theoretical Model

In every learning environment, effective feedback is a necessity in enhancing quality learning. According to Murdock & Sargeant (2012), feedback is especially useful in medical education because it enables learners to understand the particular actions that affect their ability to deliver quality patient care, thereby improving their clinical performance.

The practice of giving feedback is not new in the field of health education because it can even be traced back to the writings of various historical physicians such as Hippocrates (van de Ridder, 2008). However, before exploring more literature on feedback, it is monumental to understand how it is variously conceptualized by both educators and researchers alike.

According to The Concise Oxford English Dictionary (2011), feedback is defined as the adjustments and modifications done on a process to create an effect on it and make it deliver the desired results. This definition implies that feedback is performed to bridge the gap between the actual and desired outcome of a process. Thus, in medical education, feedback refers to the delivery of information to students about their work; to acknowledge the differences and similarities between the actual and desired outcomes of any given academic work (Baud & Molley, 2013). Based on these definitions, it is possible to extrapolate that feedback is not only about making inputs but also entails a consideration of the effects that the inputs have on the results. With this regard, Baud (2015) asserts that trainers who provide feedback to medical students can only know that learning has occurred from the feedback when the students work towards bringing out the desired learning outcomes, thereby leading to the completion of the feedback loop.

A major theoretical perspective taken by researchers when evaluating the effectiveness of learning feedback is the Kolbe’s learning cycle. According to McKimm (2009), the Kolbe’s learning cycle is used in the context of adult learning and holds that adults learn cyclically through four major stages as illustrated in the below:

The first stage is concrete experience; McKimm (2009) illustrates that in this stage of the learning cycle, learners may not have adequate knowledge on the subject, and are more likely to make mistakes. Therefore, they should learn from simulations, books, lectures and experienced people.

The second stage is reflective observation. At this stage, learners can reflect on whatever they have learned. During this reflection process, they try to evaluate whether they clearly understood the concept, or try to analyse other people’s reactions to the concepts. Therefore, according to Kolbe’s learning cycle, this stage involves the student’s application of the knowledge to real patients and tries to find any opportunity of improving their skills.

The third stage of Kolbe’s learning cycle is abstract conceptualization. Here, students begin to think of anything that could have been done differently, or if there is anything within the process that could be altered. For example, students in this stage of the learning cycle could evaluate whether there is an alternative technique for opening the abdomen of a patient with multiple abdominal scars. Nonetheless, the last stage of Kolbe’s learning cycle is the active experimentation stage. Learners who have reached this stage attempt to develop and test new ideas of solving the problem.

Feedback plays an important role in Kolbe’s learning cycle because the learners rely on feedback to reflect and take part in other processes in the cycle. Unfortunately, though, Murdock & Sargeant (2012) observe that Kolbe’s learning cycle fails to consider how and where the learner gets the experience. This means that the theory fails to consider both unconscious learning and retrospective reflection, all of which are important aspects of the learning process.

Apart from Kolbe’s learning cycle, another theoretical perspective held by researchers in the field of education is that learners use feedbacks differently depending on how senior they are in the program. According to Murdock & Sargeant (2012), trainees in the earlier levels of their training may have a negative perception towards negative feedback and have a positive attitude towards positive feedback because it reassures them. Alternatively, trainees at senior levels may take feedback as an important contributor to their personal development and may have more preference to verbally and immediately delivered informal feedback (Murdock & Sargeant, 2012).

Against this backdrop, researchers have identified and documented several models of feedback delivered to learners in a classroom environment. As illustrated in the following sections, these models have been developed over time to ensure that feedback is delivered constructively.

Models for Delivering Feedback

One model that is commonly used by educators is the feedback sandwich model. Parkes et al, (2013) observe that in this model, the learner is chronologically taken through the learning event and feedback is delivered within each stage of the process. This strategy is considered effective in one on one feedback sessions to enhance the learner’s concentration capabilities.

The other model that is recognised by existing literature is Pendletpon’s rule. Coined in 1984, the model was developed to facilitate the provision of feedback to medicine students within the life support speciality (Parkes et al, 2013). While the original Pendletpon’s rule did not have any specific rules of application, its widespread use has led to the inclusion of the word ‘rules’ in the model (Parkes et al, 2013). Nonetheless, Parkes et al (2013) observes that the model is most popularly useful with students learning practical skills and follows a structure that entails the learner describing what happened according to the expectations, what they did well to the trainer’s expectation, what they could have improved on, and how these improvements can be achieved (Pendleton et al, 1984).

Researchers have identified several advantages and limitations of this model. For instance, Pendleton et al (1984) observe that the Pendletpon’s rule is useful in developing insights and assisting students to reflect on their learning experiences. However, Klaber (2012) complains that the model is too rigid. Moreover, Klaber (2012) observes that providing feedback to learners using the Pendletpon’s rule might be time-consuming and may overwhelm them with too much information is delivered.

Apart from Pendletpon’s rule and the sandwich model of feedback, existing literature has also explored the use of agenda-led and outcome-based feedback. According to Parkes et al, (2013), the model’s main target is to identify the learners’ main objective and what they want to learn through assistance. Therefore, believers in this model seek to understand the learners’ chosen learning objectives and avoid speculating what knowledge they think the learner requires. Therefore, to ensure that the learners find it easier to achieve their goals, they must have an open mind when receiving the feedback, which implies that they must avoid being defensive and understand the learning points free of their feelings (Kritek, 2015).

The last model identified by this review is the Student-centred model. This model bestows the learner the full responsibility to the feedback process including seeking, receiving and benefiting from the feedback (Klaber, 2012). Therefore, according to Klaber (2012), this model considers three elements of feedback that the learner must execute, namely responsiveness, reflectiveness and receptiveness, thereby demonstrating self-efficacy.

The characteristics of effective feedback

Literature explores some of the fundamental characteristics of effective feedback that must be considered when developing a personalised feedback system for medical students. According to Klaber (2012), effective feedback must be based on direct observations, clear and specific. Furthermore, McKimm (2009) asserts that the feedback must specifically be targeted at the performance and not the individual while ensuring that it does not entail any judgemental language.

In the literature by Baud & Molley (2013), observations are made that effective feedback should be less evaluative and more descriptive while focusing more on the learner’s positive aspects. This implies that when giving feedback, educators should acknowledge and reward positive behaviour, thereby enhancing the learner’s confidence over their skills, and enabling them to identify areas for improvement (Baud & Molley, 2013).

The feedback can be delivered by different stakeholders, including parents, trainers, inter-professional teams and patients. Whether the feedback is formally or informally delivered, effective feedback must adhere to some principles that follow the acronym: PROMPTED (Rudland et al, 2013). The following is an illustration of the principle:

P- Represents being precise and specific to the point

R- The feedback must be relevant to the underlying practice speciality the learner is training over

M- The feedback must be measurable to identify the extent to which any improvements have

occurred

P- The feedback must be possible or achievable

Furthermore, literature by Baud & Molley (2013) indicates that when delivering informal feedback to the learner, there are specific considerations that must be made to ensure that the feedback achieves its purpose. For instance, the trainer must evaluate whether the leaning procedure goes as expected and whether there are opportunities for improvement if the knowledge is delivered again.

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. Whilst the questinnaire will be behavior-based, it will contain specific questions designed to evaluate the student’s attitudes regarding the proposed individualized feedback tool. This implies that the study will use both qualitative and quantitative research approaches as illustrated in the subsequent sections.

Several theoretical underpinnings justify the use of qualitative approaches (i.e, survey questionnaires with open-ended questions) in the proposed study. First, Apan et al (2012) argue that questionnaires are a 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 with both likert scale and open-ended questions will be the most effective tools in gauging the respondent’s behavioral response and attitude towards the tool respectively.

Due to the use of questionnaires with both Likert scale questions and open-ended questions as methods of data collection, the study is expected to take a mix of interpretive and positivst 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. On the other hand, the positivist paradig will be useful on the quantitative aspect of the study (i.e. the Likert Scale). Because the positivist paradigm relies on precise observations and verifiable measurements (Bloor & Wood, 2006), the resecher will rely on the positivist paradigm as a means of ensuring that the tool’s effectiveness is measurable.

Sampling

The researcher will conduction of one questionnaire survey for two purposes, namely to measure the effectiveness of the tool through a likert scale, and to evaluate the atitudes and perception of the respondents through open-ended questions. The questionnaire will be administered to a convenience 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 convenience 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.

Data Analysis

The proposed study will rely on mixed methods (i.e. statistical methods and thematic analysis) 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 use 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 the education of medical students, 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 against 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.

On the other hand, thematic analysis will be useful in analysis the interview responses on attitudes and perceptions. This imples that the collected data through open-ended questions will be coded and organized into categories or thems.

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 survey quality, will be maintained.. 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 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 important 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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