Semi-automatic generation of quizzes and learning artifacts from Linked Data

In this position paper, we illustrate how Linked Data can be effectively used in a Technology-enhanced Learning scenario. Specifically, we aim at using structured data to semi-automatically generate artifacts to support learning delivery and assessment: natural language facts, Q&A systems and quizzes, also used with a gaming favour, can be creatively generated to help teachers and learners to support and improve the learning path. Moreover, those artifacts can in turn be published on the Web as Linked Data, thus directly contributing to make the Web a global data space also for learning purposes

Sherlock : a Semi-Automatic Framework for Quiz Generation Using a Hybrid Semantic Similarity Measure

Acknowledgments This work is supported by the BBC Connected Studio programme (http://www.bbc.co.uk/partnersandsuppliers/con nectedstudio/), the award made by the RCUK Digital Economy theme to the dot.rural Digital Economy Hub; award reference EP/G066051/1, the award made by UK Economic & Social Research Council (ESRC); award reference ES/M001628/1, National Natural Science Foundation of China (NSFC) under Grant No. 61373051, and the China National Science and Technology Pillar Program (Grant No. 2013BAH07F05). The authors would like to thank Ryan Hussey for the work on the user interface design and Tom Cass and James Ruston for the help in developing the Sherlock application. We are also grateful to Herm Baskerville for creating the editorial quizzes and Nava Tintarev for many helpful discussions on the human evaluation.Peer reviewedPublisher PD

Exploration of Sensemaking in the Education of Novices to the Complex Cognitive Work Domain of Air Traffic Control

Many current complex business and industry jobs consist primarily of cognitive work; however, current approaches to training may be inadequate for this type of work (Hoffman, Feltovich, Fiore, Klein, & Ziebell, 2009). To try and improve training and education for cognitive work, Klein and Baxter (2006) have proposed cognitive transformation theory (CTT), a learning theory that claims that sensemaking activities are essential for acquiring expertise that is adaptive and thus well suited for cognitive work domains. In the present research, cognitive task analysis methods were used to identify and assess sensemaking support in the instruction and learning of complex concepts by two experienced air traffic control professors and seven of their students. The goal of this research was to compare instructional strategies used in an academic setting with the predictions of CTT to gain insight into strategies for the application of CTT. Cognitive task analysis methods employed included course observation, artifact examination, and knowledge elicitation sessions with two professors and seven of their students. Knowledge elicitation transcriptions were coded using categories derived from CTT and the data/frame theory of sensemaking (e.g. Klein, Moon, & Hoffman, 2006; Sieck, Klein, Peluso, Smith, & Harris-Thompson, 2007) to assess theoretical and applied implications for learning and instruction in a complex domain. Findings are represented by synthesizing theory driven predictions with grounded training strategies and technologies. In addition, recommendations are advanced for applying CTT to training and educational systems in order to provide sensemaking support during early phases of learning from which expertise may be developed

Monitoring for awareness and reflection in ubiquitous learning environments

Producción CientíficaDespite the educational affordances that ubiquitous learning has shown, it is still hampered by several orchestration difficulties. One of these difficulties is that teachers lose awareness of what the students perform across the multiple technologies and spaces involved. Monitoring can help in such awareness, and it has been highly explored in face-to-face and blended learning. Nevertheless, in ubiquitous learning environments monitoring has been usually limited to activities taking place in a specific type of space (e.g., outdoors). In this paper we propose a monitoring system for ubiquitous learning, which was evaluated in three authentic studies, supporting the participants in the affordable monitoring of learning situations involving web, augmented-physical, and 3D virtual world spaces. The work carried out also helped identify a set of guidelines, which are expected to be useful for researchers and technology developers aiming to provide participants’ support in ubiquitous learning environments

How Student-to-Teacher Interactions Encourage Self-Regulated Learning in One Computer-Based Alternative Program

The purpose of this exploratory case study was to examine how student-to-teacher interactions encourage students to develop self-regulated learning (SRL) habits and skills. Zimmerman\u27s social cognitive theory of SRL, which supposes a relationship between academic success and SRL, is used as a conceptual framework. The representative case is a computer-based alternative education program for students at risk of dropping out of high school in grades 10-12. The teachers worked one-on-one with students in a computer lab while the students engaged in mastery-based learning using Apex Learning Inc. digital curriculum. Five teachers responded to three questionnaires to examine how student-to-teacher interactions influenced student-to-content interactions, and students\u27 forethought, performance, and evaluation behavior. The teachers also submitted instructional artifacts and described instructional tools, activity types, and scaffolds within the digital curriculum. After analysis of primary and secondary data, the results showed the following: Student-to-teacher interactions encouraged students to engage in forethought behaviors associated with goal setting and strategic planning; examples of performance behaviors were using the content to increase understanding, navigating the content efficiently and effectively, monitoring the use of task strategies, and developing thinking steps; and examples of evaluative behaviors were calibrating and making accurate self-judgments. The study can promote social change by helping students at-risk of dropping out of school develop SRL strategies correlated to academic achievement and high school graduation. SRL habits are transferable to everyday behaviors associated with continued employment, maintaining healthy relationships, and lifelong learning