Online Learning Approaches for Science, Engineering and Technology in Distance Education Online learning has been adopted in distance education worldwide. The rise of the use of digital technology in teaching and learning has enabled distance education institutions to adopt online learning to reduce costs and improve student success. The purpose of this paper is to investigate appropriate teaching approaches that could be applied in an online learning model to achieve the desired success in student progress without reducing student autonomy. The results of this study indicate that cognitivism, social constructivism and connectivism form the basis of relevant teaching approaches in the 21st century with regard to curriculum and material design. The success of the studentsu0027 learning is determined by the conducive environment created by the educators using technological means. Teaching approaches, such as community of practice, the integrative approach, apprentice and experiential learning, project and problembased approaches, as well as a competencybased approach, seem to dominate the Science, Engineering and Technology (SET) environment in the online teaching space. Students and their lecturers continue to engage after their formal interaction on an online platform.

A LearnablebyDesign (LEAD) Model for Designing Experiments for Computer Science Labs India graduates 1.5 million engineering students every year, majority of them from its Tier 2 and Tier 3 colleges where there is severe shortage of qualified faculty and lab infrastructure, and where English is second or third language for most students. To provide affordable virtual laboratories to these engineering colleges, Government of India runs the Virtual Labs project with a select set of participating institutions to create virtual labs required for entire engineering student population of India. The program suffers from two problems: 1) lack of focus on pedagogy and learnability of labs being created, and 2) little ability to scale to more teachers and subject matter experts to produce labs aligned to local contexts. This paper presents a model (LEAD model) for the design of virtual labs for a data structures and algorithms course in computer science and is intended to address the problems stated above. The model encodes the principles of learning in the design and structure of an experiment so that labs can be learnable by design. The model is based on constructivist theory of learning. It uses Bloomu0027s Taxonomy for defining learning objectives and applies Merrillu0027s first principles and Gagneu0027s 9 events of instruction as instructional design methodologies. To ensure tasks in an experiment indeed aid learning, the model requires a mapping between tasks and learning principles to be created and published along with the experiment. The model uses a pedagogy that lays strong emphasis on conceptual understanding without the use of code or program. To demonstrate the efficacy of this model, we present the data analysis of the feedback from early users of one the experiments. Even though limited in scope, data shows that experiments built using LEAD model can aid understanding for the students.