Outcome-Based Quality Assessment Framework for Higher Education

term in those days. The traditional concept of quality was inferred from the fact that world-class universities like Harvard and Oxford were considered benchmarks and no further dissection on the dimensions of quality was done. (Green 1994). Green (1994) gave an extensive analysis of the literature that defines the term quality and categorized them into the following five approaches (1) Conforming to standards in terms of the educational process and outcomes (2) Befitting the purpose This is a contradictory definition as most scholars feel that if the institution meets standards, it fits its purpose, which may not always be the case. (3) Ability to meet set institutional goals and having a clear vision (4) Meeting the needs of the customer or student It is important to state here that the student can be considered a product, customer or both from the higher education institution. (5) The traditional concept which defines quality as strive for excellence In order to elaborate on the quality dimensions for higher education, Owlia and Aspinwall (1996) gave a conceptual framework. The six dimensions identified by this framework comprise of the following – (1) Tangibles which include infrastructure, ease of access and supporting infrastructure and facilities (2) Competence which includes student-staff ratio and quality of staff along with their ability to communicate effectively with students (3) Attitude which includes guidance and willingness to help (4) Content which includes curriculum, cross-disciplinarily of knowledge and relevance of courses for future jobs (5) Delivery which includes effective communication, student feedback and providing encouragement to students (6) Reliability which includes matching goals and handling complaints Another perspective that needs to be taken into account while defining quality is that of the stakeholders. In the higher education context, academics’ and students are the stakeholders. However, student’s perspective on quality is considered much more important (Elassy 2015). The conceptual framework (Owlia and Aspinwall 1996) caters for dimensions from a service-oriented point of view. However, the product-oriented dimensions have not been included. Related studies that cover higher education service quality dimensions include O’Neill and Palmer (2004), Telford and Masson (2005) and Angell et al. (2008). Teeroovengadum et al. (2016) gave one of the most recent frameworks built upon the conceptual framework given by Owlia and Aspinwall (1996). This work presents an extensive Higher Educational Quality Assessment Model (HEQAM). One of the objectives of this model is career prospect of which one of the sub-objectives is perspective for professional career. However, it only covers career prospects from the perspective of tailoring the courses to meet market demands, ignoring the evaluation of the course from the perspective of how well passed out students have done in their professional careers after the completion of their courses. Proposed Quality Framework In view of the definition of quality for higher education given in the previous section, it can be understood that student is not just the customer of the system; he or she is also the product. Therefore, quality assessment and evaluation from the product perspective needs to evaluate the performance of the product. The proposed framework measures quality by computing quality scores for every student who passes out of a university in a given academic year. This score is calculated using the ranking of the organization that the student joins after passing out. These scores are cumulatively analysed to assess the average quality score for the organization. Moreover, a year-wise analysis can provide trends and predictions in this regard. The content dimension of quality, which includes ‘relevance of courses for future jobs’ given by Owlia and Aspinwall (1996) is quantitatively evaluated using the quality score. Consequently, quality monitoring can be performed using analytics. Higher Education System – Inputs and Outputs The higher education system can be broken down into three academic categories namely, undergraduate, postgraduate and research. The progress pathway of a student from one academic category to the next is shown in Figure 1. Students admitted to undergraduate courses in a university, upon completion, may either choose to join a postgraduate course in the same or another university, take up a job or not pursue anything at all. Figure 1 – Breakdown of Higher Education System Similarly, postgraduate course students may choose to take up a job, pursue research in the same or a different university or not pursue anything at all. Evidently, there are two transitional states. The first state of transition (Transition 1) is when a student completes an undergraduate course. However, the state when a postgraduate student completes a course can be considered the second state of transition (Transition 2). This transition diagram forms the basis of the proposed quality metric and analytical framework. From this diagram, three academic categories of students can be formulated. These academic categories include Students Pursuing Higher Education (SPHE), Students Opting For Jobs (SOFJ) and Students With No Data Available (SWNDA). SPHE includes students who choose to pursue a postgraduate degree after undergraduate degree or research after postgraduate degree. SOFJ includes students who opt for oncampus placements or get an off-campus placement in the following academic year. Therefore, all students who are able to find an industry position within one year of leaving college are considered under this academic category. The last academic category, SWNDA, includes students who do not fall under the other two academic categories. Since, this is an yearly analysis, any student who finds an offcampus placement after one year, chooses self-employment or does nothing at all for the first year after graduation, is considered under this academic category. This academic category has been added for comprehensiveness. However, for simplicity sake, the quality score for this academic category of students is taken as zero. Understandably, self-employment is a special case scenario. However, even if the student takes up self-employment within the first year of leaving the university or institution, there is no parameter to judge the success of his or her venture in the given time period. Therefore, a more detailed framework shall be required for calculating quality score for the self-employed. Quality Score (QS) Metric for Quality Assessment This research paper proposes a metric termed as ‘quality score’, which shall be calculated at student level on the basis of the transition outcome of the student from one state to another. The quality scores for students enrolled to a university shall be calculated year-wise on a scale of 1 to 10 and used for further analytics. Quality score calculations for SPHE and SOFJ academic categories of students have been provided in the following sections. Quality Score Calculation for SPHE As mentioned previously, students, upon completion of their undergraduate or postgraduate degrees are expected to pursue higher education or opt for campus placements. University or institute rankings are provided by Government organizations and private ranking agencies on a yearly basis. In order to ensure and maintain authenticity of the base data used for analysis, ranking provided by Government agencies is recommended for SPHE. Moreover, a student may move to a university in the same country or may opt to study abroad. In order to accommodate this case, the data for world university ranking must be taken for score calculation if the student is taking admission abroad and country-wise ranking shall apply in the other case to accommodate for maximum universities. In order to calculate QS for every student, the rank of the university in which the student is taking up a postgraduate degree or pursuing research and the maximum rank assigned by the ranking to any university are required as inputs. If the university in which the student is taking up postgraduate degree or research is not ranked in the list, the value zero is assigned to quality score for that student. The value of QS for a SPHE student with a known university rank is calculated by performing linear scaling. The formulae used for linear scaling (PennState 2017) are as follows – rate = scaledmax−scaledmin inputmax−inputmin (1) offset = scaledmin − (inputmin ∗ rate) (2) ouput = (input ∗ rate) + offset (3) The derivation of the formula for QS calculation in this scenario is given below. The value of variables used in equations (1), (2) and (3) are as follows –