A Ubiquitous Learning Analytics Architecture for a Service-Oriented MOOC Platform
As Massive Open Online Courses (MOOCs) generate a huge amount of learning activity data through its thousands of users, great potential is provided to use this data to understand and optimize the learning experience and outcome, which is the goal of Learning Analytics. But first, the data needs to be collected, processed, analyzed and reported in order to gain actionable insights. Technical concepts and implementations are rarely accessible and therefore this work presents an architecture how Learning Analytics can be implemented in a service-oriented MOOC platform. To achieve that, a service based on extensible schema-agnostic processing pipelines is introduced for the HPI MOOC platform. The approach was evaluated regarding its scalability, extensibility, and versatility with real-world use cases. Also, data privacy was taken into account. Based on five years of running the service in production on several platform deployments, six design recommendations are presented which can be utilized as best practices for platform vendors and researchers when implementing Learning Analytics in MOOCs.
Mobile learning in context
The widespread use of mobile technologies has led to an increasing interest in mobile learning. Context is a central topic of research in that area. In fact, a major benefit of mobile devices is that they enable learning across contexts. In this paper, we explore how context can deliver significant benefits in mobile learning and provide an extensive review of the current literature and research on mobile learning in context. Furthermore, we identify various challenges and research opportunities in this area and propose the conceptual framework CAMeL for context-aware mobile learning.
Kinematic Modelling and Simulation of a 2R Robot Using SolidWorks and Verification by MATLAB / Simulink Regular Paper
The  simulation  of  robot  systems  is  becoming very popular, especially with  the  lowering of  the cost of computers,  and  it  can  be  used  for  layout  evaluation, feasibility studies, presentations with animation and off‐ line programming. The  trajectory  planning  of  redundant manipulators  is  a very  active  area  since  many  tasks  require  special characteristics  to  be  satisfied.  The  importance  of redundant manipulators has  increased over  the  last  two decades  because  of  the  possibility  of  avoiding singularities  as  well  as  obstacles  within  the  course  of motion.  The  angle  that  the  last  link  of  a  2  DOF manipulator makes with the x‐axis is required in order to find the solution for the inverse kinematics problem. This angle  could  be  optimized  with  respect  to  a  given specified  key  factor  (time,  velocity,  torques)  while  the end‐effector  performs  a  chosen  trajectory  (i.e., avoiding an obstacle) in the task space. Modeling  and  simulation  of  robots  could  be  achieved using  either  of  the  following  models:  the  geometrical model (positions, postures), the kinematic model and the dynamic model. To  do  so,  the  modelization  of  a  2‐R  robot  type  is implemented. Our main  tasks  are  comparing  two  robot postures with the same trajectory (path) and for the same length  of  time,  and  establishing  a  computing  code  to obtain the kinematic and dynamic parameters. SolidWorks  and MATLAB/Simulink  softwares  are  used to check the theory and the robot motion simulation. This  could  be  easily  generalized  to  a  3‐R  robot  and possibly therefore to any serial robot (Scara, Puma, etc.). The verification of the obtained results by both softwares allows  us  to  qualitatively  evaluate  and  underline  the validityof  the  chosen  model  and  obtain  the  right conclusions. The results of  the simulations are discussed and an agreement between the two softwares is certainly obtained.