The Wiley Handbook of Sustainability in Higher Education Learning and Teaching. Группа авторов

presents the SLOs for each assignment component. This course also helped the students to attain programming skills since the theoretical fundamentals were practiced in a MATLAB environment.

Table 3.3 Specific SLOs of the recorded version of response to the assignment in CSE 5X08.

SLOs	Number of students performing at different levels
Average	Excellent	Outstanding	Not exhibited
Fundamental/conceptual knowledge of the topic	18	11	07	06
Communication/presentation skill	10	18	09	05
Knowledge of mathematical concepts used	17	12	06	07
Critical thinking	12	07	04	19
Programming skill	17	15	08	02

      

      The programming skill assessment component was also evaluated with the help of a structured assignment of tasks. The fundamental concepts covered in the class were formulated as major problem statements to be solved using either MATLAB or PYTHON, whichever the students were more comfortable with. This could help the students in developing strong programming skills and this aspect was observed while examining the programs, their concepts, algorithms, and application.

      So, the ways in which the courses were conducted and assessed, as discussed, could truly helped in assessing the attainment of SLOs in the students. The attainment of SLOs is being emphasized because they empower students and make them competent so that they can enjoy a sustainable career growth. We know that the OBE framework is of great importance in achieving sustainable goals of higher education; moreover, the SLOs and their mapping with POs and COs play an even more important role in determining if students can actually demonstrate what has been taught or delivered to them.

      The SDG 4 agenda highlights objectives of sustainability in education that talk about the specific set of skills to exist in learners in the education system (Tom et al. n.d.; TWI2050 – The World in 2050 2018; Franco et al. 2019; Kioupi and Voulvoulis 2019). Major competencies that were set as learning objectives under SDG 4 are:

       Critical thinking and system thinking competence

       Strategic and collaboration competence

       Anticipatory and strategic competence

       Problem‐solving and self‐awareness competence

If the above competences are seen in context with the case studies of mapping SLOs and objectives then we find that critical thinking, problem‐solving, self‐awareness, and collaboration can be seen and measured very clearly using the tool that has been discussed in the two courses. These two were not the only courses using this approach; the same or similar schemes were adopted in many other courses and SLOs were evaluated honestly.

      Another initiative, TWI2050 (The World in 2050; 2018), discusses the transformative approaches and measures that can be used to achieve SDG 4 goals for higher education. The key domains of TWI2050 are listed as:

       Human capacity and demography (Franco et al. 2019): This is related to the development of human capital and associated demography with elated human resources.

       Consumption and production (UNESCO 2019): This is directly associated with the economy and also indirectly impacts the area of education.

       Decarburization and energy (Coughlan 2011): The impact of OBE also lies in responsibility toward nature by utilizing energy optimally.

       Food, biosphere, and water (Marshall and Oxfam Education 2019).

       Smart cities (Carminati et al. 2021) (Ullo and Sinha 2021).

       Digital revolution (UNESCO 2016).

      All the above domains are correlated with SDG 4 one way or another because education and its transformation affect all the above sectors of growth and sustainability. Human capacity and human resources at the top of the list are the most precious resource that governs all other domains because the enhanced human capital will add to every other domain of the transformation listed in the TWI2050.

      3.2.3 Question Level Mapping with CEOs and COs

      Mapping becomes very relevant when it is performed at the question level, as each question in the test or in any of a course's examination component will be associated with one of more specific objectives and outcomes, that is CEOs and COs, the latter being expected to be attained on completion of the course. The COs will be subset of POs of the program under which the course is offered. For example, in a course called Signal Processing (ECE 4X09), named as SP, there are number of examination components and CE is one of them. In the CE, there are the following questions:

       Q1, Q2, Q4, Q5, Q7, Q9 are descriptive questions.

       Q3, Q6, Q8 are objective questions.

       Q10 is a numerical question.

      The questions are set in such a manner that each question aims at assessing a certain SLO or CO in the student. The questions which are descriptive can have multiple parts, such as (a), (b), etc., or a single conceptual or design question. In either case, each question or part of the question must aim at assessment of a specific outcome of the student, which requires a lot of participation and effort from the teacher concerned with the course. In the course SP, if the COs articulated by the faculty are CO1, CO2, and CO3 and the objectives are CEO1, CEO2, CEO3, and CEO4, it becomes essential that each question be mapped with some CEOs, and attainment of a particular CO or multiple COs should be carefully evaluated while examining the answer book of a candidate. So, in the course SP, the following observations were reported:

       Q10 was associated with CO3 and it was evaluated whether the student has developed this. This indicates the ability of applying a problem statement and the data given, and solving the problem accordingly. The CO3 was mapped with CEO1 and CEO2 and it was found that the extent of the correlation was 77% while mapping the CEO1 and CO3. For mapping between CEO2 and CO3, the situation was found to be somewhat bleak, namely at 54%.

       The objective questions Q3, Q6, and Q8 were mainly associated with CO1 for attaining some fundamental knowledge of signal processing. The objective questions were not direct or rote‐learning based but required lot of thinking and analysis. The students could answer these questions only if the course was fundamentally strong for the candidate. In addition, the mapping was estimated between CO1 and the related objectives CEO2. For questions Q3, Q6, and Q8, we observed the percentage of mapping as 34, 67, and 46% respectively for one candidate among 120 students. This indicates that the attainment for this student is satisfactory in Q6 but needs improvement for the other two questions.

       Similarly, we performed the analysis and mapping assessment for Q1, Q2, Q4, Q5, Q7, and Q9 which are descriptive questions.

      3.2.4