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Engineering graduates are expected to have certain attributes in addition to technical expertise that includes development in personal and interpersonal skills with societal concern. Pedagogical strategies have been continuously evolving to improve the graduate attributes. An efficient framework for blended learning that improves the graduate attributes is the need of the hour now.

A blended course model based on TPACK is proposed and the same is evaluated with Kirkpatrick evaluation method to assess the attainment of the attributes. A mapping strategy is developed for the relation between course outcomes and graduate attributes. The proposed model is tested with “Microcontroller” course in undergraduate program with students of three consecutive years in three different learning environments: offline, online and blended. The performance of the students in assessments, students’ feedback and their interest towards additional learning, project skills and job recruitment are the different elements taken for analysis.

The results obtained show that the impact of the proposed blended learning framework in improving the graduate attributes is greater than the offline environments. The analysis is done based on Kirkpatrick evaluation, which demonstrates the improvement in graduate attributes in blended learning by 18% compared to offline mode.

It is seen that blended learning shall be implemented using TPACK model effectively and the proposed model results in improvement of graduate attributes. Though the findings are good enough, the case study is limited to a particular organization and so, the various underlying parameters may vary for different institutions.

The methodology proposed is viable in any institution and may be tested for any program. The effectiveness of the blended learning is known and in this case study, the analysis from the course to the level of program is done.

The research work highlights the integration of technology, pedagogy and content knowledge to enhance engineering students' skills. Hence, it explores a new required norms of education, potentially shaping future teaching learning methodologies. By employing the Kirkpatrick evaluation, it offers insights into the model's effectiveness and influences educational practices in the need of the hour.

The proposed method and results signifies an innovative endeavor that combines technological expertise, pedagogical methods and subject matter knowledge to enhance the attributes of engineering graduates. Kirkpatrick evaluation adds a distinct dimension by objectively assessing the model's impact. The results are analyzed from the original data obtained from a particular institution.

The purpose of this research study is to explore simple collaborative technique for teaching mathematics and thus improving the problem solving skills of the students. Better pedagogic activities are required to motivate the students to perceive mathematics as a subject that stimulates problem-solving skills required for engineers.

This paper presents a research study on the application of technology-supported collaborative learning in improving the problem-solving skills of first-year engineering students in a mathematics course. The experiment was conducted in a mathematics course “Engineering Calculus” with 286 first-year engineering students in two groups: experimental group (N = 60) and controlled group (N = 226). The academic performance of the students was measured and analyzed with statistical techniques.

From the results obtained, it was found that the academic performance of the experimental group was better than the controlled group. Also, interest shown by the students in the topic that dealt with collaborative learning was more than in other topics taught using conventional teaching methods.

The teachers are required to find effective pedagogical activities to improve the problem-solving skills in mathematics. The research work proposes a collaborative method in mathematics for attaining higher cognitive level in an entry level engineering course. The limitation of this study lies in group formation techniques and the grading policy which deals only with individual assessment scores.

Practice of collaborative learning is made easy with simple technology. A clear strategy for the conduct of collaborative learning sessions has been presented. The solutions recommended are practically feasible and does not require any special infrastructure or specific training.

Using technology in mathematics teaching may not be very easy for all teachers. Especially, for an undergraduate engineering fresher, mathematics may not be a very easy task. This work shall bridge the gap with simple technology-assisted collaborative learning. The teachers need not spend too much time and effort in learning technology for mathematics teaching. The effect of this learning is significant in terms of the performance and satisfaction evaluation.

This work presents a systematic implementation of collaborative learning that shall result in improved problem-solving skills and engaging learning sessions. The statistical analysis methods and the visualization of obtained results shall help in understanding the implications of the presented work. Practice of collaborative learning is made easy with simple technology. The solutions recommended are practically feasible and does not require any special infrastructure or specific training.

The purpose of this study is to assess the incorporation of fiber reinforced polymer (FRP) bars in concrete as a reinforcement enhances the corrosion resistance in a concrete structure. However, FRP bars are not practically used due to a lack of standard codes. Various codes, including ACI-440-17 and CSA S806-12, have been established to provide guidelines for the incorporation of FRP bars in concrete as reinforcement. The application of these codes may result in over-reinforcement. Therefore, this research presents the use of a machine learning approach to predict the accurate flexural strength of the FRP beams with the use of 408 experimental results.

In this research, the input parameters are the width of the beam, effective depth of the beam, concrete compressive strength, FRP bar elastic modulus and FRP bar tensile strength. Three machine learning algorithms, namely, gene expression programming, multi-expression programming and artificial neural networks, are developed. The accuracy of the developed models was judged by R², root means squared and mean absolute error. Finally, the study conducts prismatic analysis by considering different parameters. including depth and percentage of bottom reinforcement.

The artificial neural networks model result is the most accurate prediction (99%), with the lowest root mean squared error (2.66) and lowest mean absolute error (1.38). In addition, the result of SHapley Additive exPlanation analysis depicts that the effective depth and percentage of bottom reinforcement are the most influential parameters of FRP bars reinforced concrete beam. Therefore, the findings recommend that special attention should be given to the effective depth and percentage of bottom reinforcement.

Previous studies revealed that the flexural strength of concrete beams reinforced with FRP bars is significantly influenced by factors such as beam width, effective depth, concrete compressive strength, FRP bars’ elastic modulus and FRP bar tensile strength. Therefore, a substantial database comprising 408 experimental results considered for these parameters was compiled, and a simple and reliable model was proposed. The model developed in this research was compared with traditional codes, and it can be noted that the model developed in this study is much more accurate than the traditional codes.

Replacing conventional mordants by benign mordants, rare earth (RE) salts have been used in the process of natural dyeing with annatto seed extract. The purpose was threefold – first, to increase the dye uptake through these new mordants; second, to have better fastness properties of dyed swatches and third, to have lesser effluent pollution, as the new RE mordants are used in one-tenth quantities only.

Sustainable natural dyeing was attained by using RE salts as mordant in one-tenth quantity, for natural dyeing, replacing the conventional mordants such as alum and ferrous sulphate. Annatto extract has been used as natural dye.

Through the study, it was inferred that the natural dyeing using annatto seed extract gives very good colour depth on the dyed swatches and also shows marked improvement in fastness properties.

Research implication is that often it is expected that any new chemical used in the textile processing adds on to the effluent load; however, contrary to that, this study found that the use of RE salt is very beneficial as it is used in smaller quantities, but gives far better dyeing results.

RE salts can be used in natural dyeing without causing any harm to the environment and dyers.

Use of RE salts in natural dyeing is a new concept. It is a very safe technology and can be used without causing any harm to the environment and the dyers.

This study is unique as it focuses on the use of RE salts in natural dyeing replacing the conventional mordants, which are used ten times more in quantity.

Student open feedback is an essential element to improve the teaching service. Comprehending the feedback collected daily may not be possible especially in a large classroom. There is needed an automated system that processes feedback and helps to recommend focused, precise points to the teacher stating the positives and negatives of a class. Also, the feedback texts are neither going to be grammatically correct nor going to consist only of English. Hence, an automated feedback processing system is essential that processes the mixed-language language text that provides crisp clear insights to the teachers, thus making effective student–teacher interaction.

This research is designed to analyse daily feedback from the students in grammarless English-Tamil mixed feedback and creates a dashboard that displays concise keywords regarding positive and negative aspects of the class. An ML-based system architecture is proposed for processing English-Tamil mixed grammarless feedback texts and validates the same with an experimental prototype and compares the results with other state-of-the-art models. This prototype classifies the text into different categories and provides the concise view with topic modelling techniques. This system is useful in progressive improvement of teaching learning process, subsequently leading to better teaching learning environment.

The proposed web-based architecture is validated with a prototype by comparing the results with other state-of-the-art models. The accuracy of the results is higher (>90%) in the proposed architecture than other models (<60%). The created teacher dashboard is highly recommendable and provides day-to-day recommendation for finetuning teaching and learning process. The web-based dashboard created for teachers enables them to interpret the student feedback with much ease due to the Machine learning algorithms used in implementing the web-based solution.

This system is designed to help the teachers to improve themselves in the teaching learning process with the feedback. The proposed system is a prototype that is initially tested with sample feedback texts obtained in sessions in postgraduate classrooms. The implementation of the prototype and analysis of teacher and student experience are presented as the immediate scope of this research work. This helps the teachers to get an overall view on the best teaching practices and what to improve. This work currently uses Bidirectional Encoder Representations from Transformers (BERT) uncased and in the increase of native language text the system may work with BERT multilingual.

This prototype will be implemented as a web-mobile based application. Students can submit their daily feedback through a mobile app, while teachers will access a dashboard that presents a concise overview generated by the proposed system architecture. The dashboard will also provide trend analysis, highlighting positive and negative aspects of the sessions. The system's effectiveness will be evaluated through a qualitative study, incorporating feedback from teachers and insights from students. This evaluation will help teachers gain a comprehensive understanding of the most effective teaching practices and areas needing improvement, thereby enhancing the teaching-learning process. The web-mobile application aims to Streamline the feedback process, making it easy for students to share their thoughts and for teachers to receive actionable insights. This study offers a clear and concise summary of student feedback and trend analysis from which the teachers can quickly identify patterns and make necessary adjustments to their teaching methods. Ultimately, this approach will foster a more responsive and effective educational environment, supporting continuous improvement and better student–teacher interactions. Further, the proposed system requires lesser technical knowledge and can be used by anyone.

A literature review has identified a critical need for a feedback processing system that functions at short intervals. Such a system is essential for providing teachers with concise, periodic summaries of students' open-ended feedback, which is vital for fostering continuous improvement in the teaching-learning process. The immediate processing of feedback, particularly when it contains English-mixed texts, is crucial for making timely adjustments that enhance both student performance and experience. By swiftly addressing concerns and reinforcing positive feedback, the system will improve student–teacher interactions, provide meaningful insights that contribute to progressive educational growth. This will help implement a feedback system that operates in these short intervals and allows for real-time monitoring and response to students' needs and experiences. Additionally, by highlighting areas of success, teachers can build on effective strategies and practices.

This research paper proposes a system architecture PSFAS: Progressive Student Feedback Analysis System with Multi Level Classification and Clustering that enables effective interaction between the student and the teacher with the findings from feedback and presenting an experimental prototype that can be incorporated into the regular teaching learning process, whether online or offline. It has been found from the literature review, that feedback processing is mostly done in the English language. This work proposes a system architecture that gives higher accuracy than other state-of-the art models for feedback texts having English-mix grammarless sentences.

Many researchers have reported that vitamin D can affect brain development as well as brain function. The prevalence of vitamin D deficiency in the Saudi population is 81% and it is more among women than among men. Though many studies have been done to find out the factors influencing the academic performance of Health sciences students, there is not adequate evidence regarding the influence of vitamin D level on academic performance. Therefore, this study aims to find out the association if any, between the vitamin D level and academic performance of health sciences students.

After obtaining the ethical committee approval, the data was collected from 86 female medical students, 70 female applied medical sciences students and 57 nursing students of Northern Border University. The detailed questionnaire contained the aim of the study, demographic characteristics and academic performance predictors such as self-efficacy, academic motivation, academic engagement and social engagement. The vitamin D levels were measured by an enzyme-linked immunosorbent assay (ELISA) machine (BioTek) which is available in the local hospital. The multiple linear regression analysis was used to find out the association between vitamin D levels and academic performance.

This study showed that vitamin D level had a significant association with the overall performance of the students as well as their self-efficacy.

Since there is a lot of stress among health sciences students due to subject overload and inadequacy of time, the health aspects are often overlooked. This study emphasizes the importance of early screening of vitamin D levels and early intervention in those with low vitamin D levels for better academic performance.

There is very little awareness of the impact of vitamin D deficiency on academic motivation, academic engagement, social engagement and self-efficacy among medical and health sciences students. This study can increase awareness.

There are very few studies done to find out the association between Vitamin D level and academic performance. This study is unique as it has highlighted the association between vitamin D level and grade point average (GPA) and also the association between vitamin D level and academic predictors such as self-efficacy, academic motivation, academic engagement and social engagement.

The purpose of the study is to optimize the blending ratio of Arecanut and cotton fibers to create yarn with the best quality for various applications, particularly home furnishings. The study aims to determine the effect of different blend ratios on the physical and mechanical properties of the yarn.

The study involves blending Arecanut and cotton fibers in various ratios (90:10, 75:25, 50:50, 25:75 and 10:90) at two different yarn counts (10/1 and 5/1). Various physical and mechanical properties of the blended yarn are analyzed, including unevenness, coefficient of mass variation (cvm%), imperfection, hairiness, breaking strength, elongation, tenacity and breaking work.

The research findings suggest that the blend ratio of 10:90 (10% cotton and 90% Arecanut fiber) produced the best results in terms of physical and mechanical properties for both yarn counts. This blend ratio resulted in reduced unevenness, cvm% and imperfection, while also exhibiting good mechanical properties such as breaking strength, elongation, tenacity and breaking work. The blend with a higher concentration of cotton generally showed better properties due to the coarseness of Arecanut fiber. As the goal of the study was to determine the best blend ratio that included the most Arecanut fiber based on its physical and mechanical properties, which is suitable for home furnishing applications, 75:25 Areca cotton blend ratio of yarn count 5/1 proved to be the best.

The study acknowledges that Arecanut fiber must be blended with other commercially used fibers like cotton due to its coarseness. While the study provides insights into optimizing blend ratios for home furnishings and packaging, further research may be needed to make the material suitable for clothing applications.

The research has practical implications for industries interested in utilizing Arecanut and cotton blends for various applications, such as home furnishings and packaging materials. It suggests that specific blend ratios can result in yarn with desirable properties for these purposes.

The study mentions that the increased use of Arecanut fibers can benefit the growers of Arecanut, potentially providing economic opportunities for communities engaged in Arecanut farming.

The research explores the utilization of Arecanut fibers, an underutilized resource, in combination with cotton to create sustainable yarn. It assesses various blend ratios and their impact on yarn properties, contributing to the understanding of eco-friendly textile materials.

The case helps learn various aspects of entrepreneurship, startups and startup-ecosystem in India. It also talks about challenges that a startup entrepreneur faces that others or people potential to enter business can learn. It develops one to identify diverse and holistic solutions for overcoming these challenges. Apply and explain strategies suitable to business management.

After facing lot of difficulties in personal life, Mr Mitesh Shethwala started an e-commerce business named Alagrand.com. This Ahmedabad city-based startup for selling apparels and accessories for all age group is doing so well that the valuation of company has gone beyond Rs. 20 crores. In spite of the high valuation, company is facing problem of funds and investments. The protagonist of the company has lot of plans for growing business and taking it to next level that can happen only if he gets funds for the business. The case talks about issue of investment and funding of this startup company. The company also has issues in the area of setting standard operating procedures and marketing.

Teachers can discuss this case study for various subjects like Strategic Management, Retail Management, Digital Marketing and Product and Brand Management that are taught to the students of management courses at graduate and post-graduate levels. Academicians and students should read current information and data regarding setting up startups, investment and capital budgeting related to startups and funding methods.

Teaching Notes are available for educators only.

CSS 3: Entrepreneurship.

This paper examines the social and institutional context of barriers to drug service throughcare and aftercare for prisoners in England and Wales, including those that specifically affect Black and minority ethnic prisoners. A research project in 2004 reviewed relevant literature and statistical data, mapped prison drug services, and sought the perspectives of relevant stakeholders: in total, 334 individuals were recruited to the study. The methodology facilitates analysis of the structure of services and the agency prisoner in accessing them. Recommendations are made for changes to the structure and delivery of prison drug services.