Key Action Extraction for Learning Analytics

Proceedings of: 7th European Conference on Technology Enhanced Learning (EC-TEL 2012): 21st Century Learning for 21st Century Skills. Saarbrücken, Germany, September 18-21, 2012.Analogous to keywords describing the important and relevant content of a document we extract key actions from learners' usage data assuming that they represent important and relevant parts of their learning behaviour. These key actions enable the teachers to better understand the dynamics in their classes and the problems that occur while learning. Based on these insights, teachers can intervene directly as well as improve the quality of their learning material and learning design. We test our approach on usage data collected in a large introductory C programming course at a university and discuss the results based on the feedback of the teachers.Work partially funded by the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement no 231396 (ROLE project), the Learn3 project (TIN2008-05163/TSI), the eMadrid project (S2009/TIC-1650), and the Acci´on Integrada DE2009-0051.Publicad

Short Paper: Blockcheck the Typechain

Recent efforts have sought to design new smart contract programming languages that make writing blockchain programs safer. But programs on the blockchain are beholden only to the safety properties enforced by the blockchain itself: even the strictest language-only properties can be rendered moot on a language-oblivious blockchain due to inter-contract interactions. Consequently, while safer languages are a necessity, fully realizing their benefits necessitates a language-aware redesign of the blockchain itself. To this end, we propose that the blockchain be viewed as a typechain: a chain of typed programs-not arbitrary blocks-that are included iff they typecheck against the existing chain. Reaching consensus, or blockchecking, validates typechecking in a byzantine fault-tolerant manner. Safety properties traditionally enforced by a runtime are instead enforced by a type system with the aim of statically capturing smart contract correctness. To provide a robust level of safety, we contend that a typechain must minimally guarantee (1) asset linearity and liveness, (2) physical resource availability, including CPU and memory, (3) exceptionless execution, or no early termination, (4) protocol conformance, or adherence to some state machine, and (5) inter-contract safety, including reentrancy safety. Despite their exacting nature, typechains are extensible, allowing for rich libraries that extend the set of verified properties. We expand on typechain properties and present examples of real-world bugs they prevent

Induction of Rhizobium Inoculants Harboring Salicylic Acid Gene

Abstract: In this study eight antibiotics and six heavy metals were used for genetic marking of seven Rhizobium strains and six Pseudomonas strains to be used in conjugation. Six pseudomonas strains were selected on the basis of IAA and salicylic acid production to be used as a donor against seven Rhizobium strains as recipients. All the matins between rhizobiunm and pseudomonas strains were successed except for the four matings between; RL-3841 X P.putida21, RL-4406 X P.putida21, RL-4404 X P.putida21 and RL-4404 X PF-10 which did not appeared any recombinants on selective medium. Plasmids from seven rhizobium and six Pseudomonas strains were cured using elevate

Understanding Learners’ Behaviors in Serious Games

Best paper awardInternational audienceUnderstanding play traces resulting from the learner’s activity in serious games is a challenged research area. Especially, when the serious game is characterized by a large state space and a large amount of free interactions, the play traces become complex and thus hard to analyze and to interpret by teachers. In this paper, we present a framework that assists designers to build a model of an expert’s solving process semi-automatically. Based on this model, we propose an algorithm that analyzes player’s traces in order to generate pedagogical labels about the learner’s behavior. We carried out an experimental study which aimed to evaluate the effectiveness of the labeling algorithm. From a usability point of view, we also use the experiment to validate the acceptation and readability of pedagogical labels by the teachers

On the application of financial security standards in blockchain platforms

© Springer Nature Switzerland AG 2020. Security standards such as the Payment Application Data Security Standard (PA-DSS) have been developed to keep transaction data secured in traditional payment systems. However, blockchain systems are not in the scope of these security standards. In this work, we highlight the differences between traditional and decentralized payment platforms and we present an adaptation of the PA-DSS standards to apply them in transaction-supported, decentralized blockchain platforms. We evaluate the QTUM and Ethereum blockchain platforms by using our adapted standards and we report security gaps on each platform. We conclude that neither platform is suitable for business adoption based on the adapted PA-DSS standard’s evaluation results

Fuzzy student modeling for personalization of e-learning courses

In the context of e-learning courses, personalization is a more and more studied issue, being its advantage in terms of time and motivations widely proved. Course personalization basically means to understand student's needs: to this aim several Artificial Intelligence methodologies have been used to model students for tailoring e-learning courses and to provide didactic strategies, such as planning, case based reasoning, or fuzzy logic, just to cite some of them. Moreover, in order to disseminate personalised e-learning courses, the use of known and available Learning Management System is mandatory. In this paper we propose a fine-grained student model, embedded into an Adaptive Educational Hypermedia, LS-Plan provided as plug-in for Moodle. In this way we satisfy the two most important requirements: a fine-grained personalization and a large diffusion. In particular, the substantial modification proposed in this contribution regards the methodology to evaluate the knowledge of the single student which currently has a low granularity level. The experiments showed that the new system has improved the evaluation mechanism by adding information that students and teachers can use to keep track of learning progress