Technology-Enhanced Learning Environments to Support Students' Argumentation

2007 ◽  
pp. 217-243 ◽  
Author(s):  
Douglas B. Clark ◽  
Karsten Stegmann ◽  
Armin Weinberger ◽  
Muhsin Menekse ◽  
Gijsbert Erkens
Keyword(s):  
Learning Environments ◽  
Technology Enhanced Learning ◽  
Support Students ◽  
Enhanced Learning

scholarly journals Developing a competency taxonomy for teacher design knowledge in technology-enhanced learning environments: a literature review

2019 ◽  
Vol 14 (1) ◽  
Author(s):  
Mi Song Kim
Keyword(s):  
Literature Review ◽  
Learning Environments ◽  
Teacher Educators ◽  
Teaching Practice ◽  
Design Knowledge ◽  
Technology Enhanced Learning ◽  
Design Data ◽  
Design Work ◽  
Teacher Design ◽  
Enhanced Learning

AbstractRecent research in technology-enhanced learning environments has indicated the need to redefine the role of teachers as designers. This supports successful learners better able to adapt to twenty-first century education, in particular STEM education. However, such a repositioning of teaching as a design science challenges teachers to reconceptualize educational practice as an act of design, not in the artistic meaning of the word. Our recent research finding also indicated that teacher design knowledge (TDK) processes are often invisible to both the teacher educators and the teachers. To respond to these challenges, this paper will define TDK for STEM teachers by making TDK visible in the form of a TDK competency taxonomy. A systematic literature review was conducted to identify the characteristics of teaching practices in technology-enhanced learning environments. This TDK competency taxonomy consists of four main categories drawing on existing literature on teacher design work and teacher instructional design: data practice, design practice, knowledge creation practice, and professional teaching practice. The implications of these findings were discussed.

Emerging Edtech

2011 ◽  
pp. 1880-1891
Author(s):  
Ching-Huei Chen ◽  
Manetta Calinger ◽  
Bruce C. Howard
Keyword(s):  
Instructional Design ◽  
Learning Environments ◽  
Best Practice ◽  
Design Principles ◽  
Educational Technologies ◽  
Technology Enhanced Learning ◽  
Emergent Technologies ◽  
Practice Models ◽  
How People Learn ◽  
Enhanced Learning

Design principles are universal and may be translated onto the newest trends and emergent technologies. In this research study, the authors combined the perspectives provided by two sources to create a set of recommended design principles for technology-enhanced learning environments. One source was the How People Learn framework (Bransford, Brown, & Cocking, 2000). The second source was a series of interviews conducted with pacesetters in the field of educational technologies. With the knowledge gained from these two sources, the authors created our own set of design principles. These principles may be used to guide evaluation, instructional design efforts, or best practice models for exemplary use of educational technologies in the classroom.

Principled Construction and Reuse of Learning Designs

2011 ◽  
pp. 869-890 ◽  
Author(s):  
Gilbert Paquette ◽  
Olga Mariño ◽  
Karin Lundgren-Cayrol ◽  
Michel Léonard
Keyword(s):  
Learning Environments ◽  
Learning Objects ◽  
Research Center ◽  
Technology Enhanced Learning ◽  
Learning Design ◽  
Future Directions ◽  
Enhanced Learning

This chapter summarizes the work on instructional engineering and educational modeling accomplished since 1992 at the LICEF Research Center of Télé-université by the researchers of the CICE Research Chair. Recent results on learning design modeling and learning objects reusability processes are thoroughly presented using examples drawn from many projects conducted in the last 3 years. These are discussed to uncover the importance of a principled approach for the modeling of learning design and the of learning objects in technology enhanced learning environments. Finally, delivery and dissemination issues are discussed and a summary of on-going and future directions for research is presented.

Measuring and Profiling Self-Regulated Learning in the Online Environment

2010 ◽  
pp. 27-38 ◽  
Author(s):  
Lucy Barnard-Brak ◽  
William Y. Lan ◽  
Valerie Osland Paton
Keyword(s):  
Higher Education ◽  
Academic Achievement ◽  
Learning Environments ◽  
Social Cognitive ◽  
Future Research ◽  
Technology Enhanced Learning ◽  
Cognitive Perspective ◽  
Self Regulated Learning ◽  
Enhanced Learning

While the presence of technology-enhanced learning environments (TELEs) will only increase in higher education, this book chapter examines current literature concerning the measurement of online SRL behaviors and the application of this online SRL measurement with regard to profiling SRL behaviors in TELEs. The methodologies and issues associated with the measurement of SRL behaviors in TELEs is discussed in view of extant research. The organization of SRL behaviors into five, distinct profiles is then discussed in view of a social cognitive perspective concerning the development of SRL (e.g. Zimmerman & Schunk, 2001). The book chapter concludes with recommendations for future research concerning the presence of SRL profiles and their relationship to other metacognitive factors and academic achievement.

scholarly journals Disengagement, engagement and digital skills in technology-enhanced learning

2019 ◽  
Vol 25 (2) ◽  
pp. 957-983 ◽  
Author(s):  
Nina Bergdahl ◽  
Jalal Nouri ◽  
Uno Fors
Keyword(s):  
Student Performance ◽  
Statistical Tests ◽  
Technology Enhanced Learning ◽  
Digital Skills ◽  
Strong Consensus ◽  
Low Levels ◽  
Engagement And Disengagement ◽  
Support Students ◽  
The Relationship ◽  
Enhanced Learning

Abstract With the digitalisation of education increasing, the relationship between student engagement in Technology-enhanced Learning (TEL) and digital skills has remained largely unexplored. There is a strong consensus that engagement is necessary for students to succeed in school. We hypothesised that students reporting high and low levels of general engagement display differences in terms of their engagement in TEL, and that students’ digital skills correlate with their engagement in and disengagement in TEL, which in turn is related to their learning outcomes. We used statistical tests to explore the relationship between the students’ (N = 410) general engagement and engagement in TEL, and investigated how digital skills were related to engagement and disengagement in TEL. We found significant correlations between students’ digital skills and engagement in TEL, showing that the possession of high levels of digital skill is related to engagement in TEL. Interestingly, digital skills were not related to disengagement. This suggests that students reporting both high and low levels of digital skills disengage to some extent when learning with technologies. We also identified variables reflecting both engagement and disengagement in TEL that predict student performance as measured via final grades, implying that in order to understand and support students who learn with technologies, a broader understanding of the factors influencing engagement and disengagement is key.

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