Engaging Learners with New Strategies and Tools

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Distance education is unique in design in terms of the content, communication, collaboration, and instructors’ shifting role from lecturing to coaching, mentoring, guiding, directing, and curating (Anderson, 2008; Siemens, 2008). Educators should equip the 21st century learners with cooperative, collaborative, and creative problem solving teams skills that characterize today's workforce.  To help learners share information and encourage the synergy of ideas and solutions, the online learning environment should encompass eclectic learning theories and appropriate technologies of semantic web for computer supported collaborative learning (Shinyi, & Yu-Chuan, 2013).  Anderson (2008) recommends community of inquiry model to include cognitive, social, and teaching presence, for a meaningful learning.  Siemens (2008)  proposes curatorial role to instructors, in an online environment, a transplant of many roles Chevalier (2007) ascribes to managers and leaders who wear many hats in the figure below.

The communication technology has provided various online collaborative tools at my disposal.  Most organizations are using office 365 for online and cloud computing.  The use of teleconferences and webinars might assist to communicate salient issues or educate students on written skills that are necessary for online learners.  Models for effective distance education should encompass eclectic learning theories and appropriate technologies for computer supported collaborative learning (Shinyi, & Yu-Chuan, 2013).  Strategies, which include a well-designed interactive online learning environment that provides positive attitudes and higher levels of performance through increased student interactivity, are best for engaging students as active participants in the online environment (Durrington, Berryhill, & Swafford, 2006).  Those procedures should promote learner to learners, to content, and to instructor interactions, as well as collaborative learning, community and assessment centered principles (Anderson, 2008; Darabi, & Jin, 2013).  Online instructors, as transformational leaders, should prioritize performance coaching to provide the necessary resources to enable learners to meet established SMART (specific, measurable, accepted, realistic, time-bound) goals and objectives for desired performance results (Hechanova & Cementina-Olpoc, 2013).  They should develop students’ self-efficacy to increase students’ intrinsic and extrinsic motivational tools for subject affinity, as participant rely on content, communication, and collaboration.

As a math instructor, I subscribe to adaptive learning technology that cuts across numerous fields of study such as computer science, education, and psychology (Shih, Kuo, & Liu, 2012), and enables transformative and reflective learning.  Adaptive learning is prescriptive, systematic, wholostic, and humane (Driscoll, 2005, p. 139).  In an asynchronous learning environment, it is imperative to establish learning objectives, expectations, and policies, ascertain communication and decision-making rules with implicit feedback.  Instructional designers should collaborate with subject matter experts to decide on the use of appropriate technology for the course and learning management system with collaborative tools, analyzing its strengths, weaknesses, opportunities, and threats.  The 21st century technology provides means to design dynamic content to reach more students, access electronic (digital) book, and present differentiated instruction to fit all learning styles (Garner, 2003).  Adaptive learning supports information (Layde et al., 2012), constructivism and connective principles (Downes, 2012; Siemens, 2008) learning theory and the way individuals learn.

References

Anderson, T. (Ed.).  (2008). The theory and practice of online learning.  (2nd ed.).  Edmonton, AB: Athabasca University Press.

Borup, J., West, R. E., & Graham, C. R.  (2013).  The influence of asynchronous video communication on learner social presence: a narrative analysis of four cases.  Distance Education, 34(1), 48-63.  doi:  10.1080/01587919.2013.770427

Chevalier, R. D.  (2007).  A manager's guide to improving workplace performance.  New York, NY:  American Management Association.

Darabi, A., & Jin, L.  (2013).  Improving the quality of online discussion: the effects of strategies

designed based on cognitive load theory principles.  Distance Education, 34(1), 21–36.  doi:  10.1080/01587919.2013.770429

Durrington, V. A., Berryhill, A., & Swafford, J.  (2006).  Strategies for enhancing student interactivity in an online environment.  College Teaching, 54(1), 190−193

Shinyi, L., & Yu-Chuan, C. (2013).  Distributed cognition and its antecedents in the context of computer-supported collaborative learning (CSCL).  Asian Social Science, 9(7), 107-113.  doi: 10.5539/ass.v9n7p107

Siemens, G. (2008, January).  Learning and knowing in networks:  Changing roles for educators and designers.  ITForum.

 

 

 

 

 

 

Engaging Learners with New Strategies and Tools

Distance education is unique in design in terms of the content, communication, collaboration, and instructors’ shifting role from lecturing to coaching, mentoring, guiding, directing, and curating (Anderson, 2008; Siemens, 2008). Educators should equip the 21st century learners with cooperative, collaborative, and creative problem solving teams skills that characterize today's workforce.  To help learners share information and encourage the synergy of ideas and solutions, the online learning environment should encompass eclectic learning theories and appropriate technologies of semantic web for computer supported collaborative learning (Shinyi, & Yu-Chuan, 2013).  Anderson (2008) recommends community of inquiry model to include cognitive, social, and teaching presence, for a meaningful learning.  Siemens (2008)  proposes curatorial role to instructors, in an online environment, a transplant of many roles Chevalier (2007) ascribes to managers and leaders who wear many hats in the figure below.

The communication technology has provided various online collaborative tools at my disposal.  Most organizations are using office 365 for online and cloud computing.  The use of teleconferences and webinars might assist to communicate salient issues or educate students on written skills that are necessary for online learners.  Models for effective distance education should encompass eclectic learning theories and appropriate technologies for computer supported collaborative learning (Shinyi, & Yu-Chuan, 2013).  Strategies, which include a well-designed interactive online learning environment that provides positive attitudes and higher levels of performance through increased student interactivity, are best for engaging students as active participants in the online environment (Durrington, Berryhill, & Swafford, 2006).  Those procedures should promote learner to learners, to content, and to instructor interactions, as well as collaborative learning, community and assessment centered principles (Anderson, 2008; Darabi, & Jin, 2013).  Online instructors, as transformational leaders, should prioritize performance coaching to provide the necessary resources to enable learners to meet established SMART (specific, measurable, accepted, realistic, time-bound) goals and objectives for desired performance results (Hechanova & Cementina-Olpoc, 2013).  They should develop students’ self-efficacy to increase students’ intrinsic and extrinsic motivational tools for subject affinity, as participant rely on content, communication, and collaboration.

As a math instructor, I subscribe to adaptive learning technology that cuts across numerous fields of study such as computer science, education, and psychology (Shih, Kuo, & Liu, 2012), and enables transformative and reflective learning.  Adaptive learning is prescriptive, systematic, wholostic, and humane (Driscoll, 2005, p. 139).  In an asynchronous learning environment, it is imperative to establish learning objectives, expectations, and policies, ascertain communication and decision-making rules with implicit feedback.  Instructional designers should collaborate with subject matter experts to decide on the use of appropriate technology for the course and learning management system with collaborative tools, analyzing its strengths, weaknesses, opportunities, and threats.  The 21st century technology provides means to design dynamic content to reach more students, access electronic (digital) book, and present differentiated instruction to fit all learning styles (Garner, 2003).  Adaptive learning supports information (Layde et al., 2012), constructivism and connective principles (Downes, 2012; Siemens, 2008) learning theory and the way individuals learn.

References

Anderson, T. (Ed.).  (2008). The theory and practice of online learning.  (2nd ed.).  Edmonton, AB: Athabasca University Press.

Borup, J., West, R. E., & Graham, C. R.  (2013).  The influence of asynchronous video communication on learner social presence: a narrative analysis of four cases.  Distance Education, 34(1), 48-63.  doi:  10.1080/01587919.2013.770427

Chevalier, R. D.  (2007).  A manager's guide to improving workplace performance.  New York, NY:  American Management Association.

Darabi, A., & Jin, L.  (2013).  Improving the quality of online discussion: the effects of strategies

designed based on cognitive load theory principles.  Distance Education, 34(1), 21–36.  doi:  10.1080/01587919.2013.770429

Durrington, V. A., Berryhill, A., & Swafford, J.  (2006).  Strategies for enhancing student interactivity in an online environment.  College Teaching, 54(1), 190−193

Shinyi, L., & Yu-Chuan, C. (2013).  Distributed cognition and its antecedents in the context of computer-supported collaborative learning (CSCL).  Asian Social Science, 9(7), 107-113.  doi: 10.5539/ass.v9n7p107

Siemens, G. (2008, January).  Learning and knowing in networks:  Changing roles for educators and designers.  ITForum.

 

 

 

 

 

 

https://docs.google.com/drawings/d/1xVdVbNS90ZIuDYkbXNerSmklid29fls5pceBMCH9vBM/edit?usp=sharing

STORY BOARD

STORY BOARD

file://localhost/Users/seglakossivi/Desktop/SUNCH.docx

file://localhost/Users/seglakossivi/Desktop/SUNCH.docx

Assessing Collaborative Efforts

Assessing Collaborative Efforts

According to Dr. Siemens, in the participative pedagogy, with collaboration and teamwork in curricular activities, the shit from an individual-based learning assessment model shifts to a collaborative-based learning assessment (Laureate Education, 2011).  Cooperative learningencompasses collaborative learning, peer tutoring, and other methods in which students work together in small groups to maximize their own and each other’s learning (Shinyi & Yu-Chuan, 2013).  In a collaborative learning community, students bring to the course their varying levels of skill and knowledge and become co-creators of erudition that might affect the instructor's fair and equitable assessment of learning.  Consequently, assessment will include feedback from online communities, community, peers’ assessment, and student self-assessment.

If a student does not want to network or collaborate in a learning community for an online course, the other members of the learning community might completethe missing task and report the incidence to the instructor.  The instructor might check with the student for the rationale of the behavior, or assign the student to another group.  In a learning management system, the instructor can access and assess on the number of time the students long on, hours spent, hours in-group related activities, and the number of posts students contributed.  Effective teams require both individual accountability of member contribution and mutual accountability of the overall result of the team’s effort (Oosterhof, Conrad, & Ely, 2008).  The unequal responsibility and workload among group might spur negative consequence for the team or individual.  The instructor must be transparent in assigning rubrics to the assigned work, and use fair, direct, and equitable marks, assessing from the stated outcome-based metrics. In an authentic context-based assessment, assessment becomes a teaching-based activity that provides and opportunity to give feedback and evaluate learners as well as educators (Laureate Education, 2008).  It is important to develop strategies to engage reluctant learners who might lack intrinsic motivation for active engagement in collaborative learning communities (Park, 2013) and establish extrinsic motivators by aligning with self-determination theory for integrated extrinsic motivation activities (Clara & Barbera, 2013).

References

Clara, M., & Barbera, E.  (2013).  Learning online: massive open online courses (MOOCs), connectivism, and cultural psychology.  Distance Education, 34(1), 129-136.  doi: 10.1080/01587919.2013.770428
Laureate Education, Inc.  (2008).  Assessment of Collaborative Learning.  Baltimore, MD:  Author
Oosterhof, A., Conrad, R., & Ely, D. P.  (2008).  Assessing learners online.  Upper Saddle Rive, NJ: Pearson Merrill Prentice Hall
Park, S. W.  (2013).  The potential of web 2.0 tools to promote reading engagement in a general education course.  TechTrends, 57(2), 46-53
Shinyi, L., & Yu-Chuan, C. (2013).  Distributed cognition and its antecedents in the context of computer-supported collaborative learning (CSCL).  Asian Social Science, 9(7), 107-113.  doi: 10.5539/ass.v9n7p107

Story Board: Asynchronous VS Synchronous Interactions