Learner Groups in Massive Open Online Courses

The open nature of Massive Open Online Courses (MOOCs) attracts a large number of learners with different backgrounds, skills, motivations, and goals. This has brought a need to understand such heterogeneity in populations of MOOC learners. Categorizing these learners based upon their interaction with the course can help address this need and suggest possible improvements in course design and delivery. In this article, the K-means clustering technique with careful seeding is used to obtain clusters of learners having similar interaction in the course. Learners are grouped based on their interaction with course material, video lectures, discussion forums, and assessments. In the analysis of thirteen courses, the proposed method identified learners’ classes as Uninterested, Casuals, Performers, Explorers and Achievers. Each class of learners had distinct interaction with the course and followed a certain learning approach. The learners’ classes were mapped to the standard surface, deep, and strategic learning approaches.This article also highlights the data preparation phase and its importance in data mining.     

Attitudes of secondary school teachers towards inclusive education in New Delhi,India

This study was undertaken to determine the attitudes of secondary regular schoolteachers towards the inclusion of students with disabilities in New Delhi. A total of 470 teachers, working in schools managed by a private organisation in Delhi, returned the completed survey. A two‐part questionnaire was used in this study. Part one gathered information relating to personal and professional characteristics of the teachers. Part two was a 16‐item Likert scale titled, Attitudes towards Inclusive Education Scale. The major finding of the study was that the teachers in Delhi had positive attitudes towards the inclusion of students with special needs. This study also indicated that the teachers who were more positive about inclusive education were male, younger teachers (less than 40 years of age), less experienced (less than 10 years) and had postgraduate qualifications. In addition, the teachers who had a contact with a person with a disability and those who did not have a focus on disability during their preservice teacher education programmes were more positive towards inclusive education.     

An ensemble approach in converging contents of LMS and KMS

Currently the challenges in e-Learning are converging the learning content from various sources and managing them within e-learning practices. Data mining learning algorithms can be used and the contents can be converged based on the Metadata of the objects. Ensemble methods use multiple learning algorithms and it can be used to converge the Learning Objects from Learning Management Systems (LMS) and Knowledge Objects from Knowledge Management System (KMS). This can increase the performance of the learning system, especially when there is different content available from a variety of models. In this research, Data mining ensemble techniques are used so that an appropriate learning content is delivered to the learner. By converging, the learning content from various sources the Learning system pedagogies can also be revolutionized and a right learning path can be provided to the learners. This research work uses various classification techniques for converging and are evaluated using statistical measures.     

Unidirectional motion of vehicle on sinusoidal path Can it cause illusory forward and backward motion?

The feeling of being in motion, while observing a moving train passing nearby is a common experience. It is an example of relative motion where a stationary observer experiences an illusory motion caused by a vehicle moving in the opposite direction. It is however counter-intuitive to imagine periodic changes in the direction of relative motion, while the vehicle continues to move in one direction only. To an observer, sitting inside the moving vehicle, periodic changes in direction can lead to the illusion of being in oscillatory forward and backward relative motion. This article, using a simple mathematical model describes how the unidirectional motion of vehicle on a sinusoidal path can lead to the illusion of being in periodic forward and backward relative motion. This work has emerged out of a real life experience during a train journey on the hilly curves from Kalka to Shimla.     

Choice based diffusion model for predicting sales of mobile phones using conjoint analysis

The modeling of understanding consumers buying behavior requires a technique, which does not only incorporate the preferences of the consumers but also have the ability to trade-off between multi-characteristics products and services. This study is supported by evaluating a framework via a marketing research technique of Conjoint Analysis wherein we have shown how certain attributes of mobile phones when studied jointly can affect the overall buying behavior of the youth towards various brands taken into consideration. Further, customers' choice probabilities of the mobile phones, based on preferences have been evaluated and potential market size is determined. Also, this study has determined and forecasted the sales on the basis of choice probability and utility obtained via conjoint analysis. Customers of the mobile phone located in Delhi have been targeted for this study.