Uncategorized

Defining Distance Learning

New-Mind-Map

My Personal Definition and Observations of Distance Learning.

My personal definition and observations of distance learning before this distance learning course entailed learning using technology, such as computers, tablets, mobile phones, and the Internet, where the teacher and the student do not have to be in the same location, and where the teacher and the student do not have to connect at the same time, for example, asynchronous. I think I defined it in this way, because this was the experience I had with distance learning, and self-study at a distance. I did not define it as being only offered through an educational institution per se.

In Week 1 of the Distance Learning course, I learned that what is termed distance education has a very long history, and its definition and related terms keep evolving. For example, distance education started in Europe with the use of the post to learn via correspondence study in 1833; in 1920, with the advent of electronic communications technology in the United States, the radio, television, satellite, and fiber-optic communication systems with two-way, high quality video and audio systems were also used in education. This fiber-optic system formed the foundation for computer telecommunications, and asynchronous, Internet-based programs, which are now being offered to distance learners; in 1962, the first landmark of distance teaching universities occurred, when the University of South Africa decided to become such an institution, and in 1971, the United Kingdom’s Open University decided to become a degree-offering distance teaching university (Simonson, Smaldino, & Zvacek, 2015, p. 36-39). There are also various related terms, and they are 1) E-learning, when distance education occurs in the private sector; 2) virtual education/ virtual schooling, which entails distance education in K-12 schools; 3) on-line learning/on-line education, which entails distance education in higher education (Simonson et al., 2015, p. 33); 4) distance teaching, and distance learning (Laureate education, n. d.). There are different definitions of distance education, such as those proposed by Rudolf Manfred Delling (1985), Hillary Perraton (1988), the U.S. Department of Education’s Office of Educational Research (2006), Grenville Rumble (1989), Desmond Keegan (1996), Borje Holmberg (1985), Otto Peters (1988), and Garrison and Shale (1987).

My Revised Definition of Distance Learning

          Learning using technical media, such as print, audio, video, and computers, where the teacher and the learner are physically separated, where communication can occur synchronously (through the use of webinars, and Skype), or asynchronously (through the use of discussion boards), where a two-way communication exists between and among the teacher and the learners to facilitate and support the education process, and where it can be offered either through an institution, or through the emerging definition of open learning, where it can occur outside the traditional institution of education (Simonson et al., 2015, p. 35).

My Vision for the Future of Distance Learning.

          A form of distance learning that I am personally interested in offering is e-learning, or self-study at a distance, which, as stated by Simonson (Laureate education, n. d.), entails individuals learning skills at a distance. I am interested in providing psychological skills. I also want Aruba’s university to offer distance education in the future. I think that with the Web 2.0 tools (http://oedb.org/ilibrarian/101-web-20-teaching-tools/) that are now available, distance learning will keep evolving, encompassing more collaboration between teachers and students, and between students, and the creation of a solid community of learners on-line.

 

 

References

Open Education Database (n. d.). 101 Web 2.0 Teaching Tools. Retrieved from

http://oedb.org/ilibrarian/101-web-20-teaching-tools/

Simonson, M., Smaldino, S., & Zvacek, S. (2015). Teaching and learning at a distance:

Foundations of distance education. Charlotte, NC: Information Age Publishing, Inc.

Laureate Education (Producer). (n.d.). Distance education: The next generation [Video file].

Retrieved from https://class.waldenu.edu

 

Uncategorized

Evaluating and Identifying Online Resources

brain1-mantleThe second week of the Learning Theories and Instruction course covered the topics of the brain and learning, how the brain processes information, and how we solve problems.

For the second assignment, I am going to comment on some very interesting academic journal articles about brain research and learning, information processing in the brain, and problem-solving. I will discuss two articles for each of the three topics.

The first article about brain research and learning is titled Formal Learning Theory Dissociates Brain Regions with Different Temporal Integration by Jan Glascher and Christian Buchel. The researchers created an experiment using fMRI (Functional magnetic resonance imaging) to study Pavlovian fear conditioning where reinforcement incidents were fully varied during the experimental course. The researchers used the formal learning theory (Rescorla-Wagner model) as their theoretical framework. Using the fMRI and this theoretical perspective, they found that learning-related brain regions, such as the amygdala, which is involved in long temporal integration, and the higher perceptual regions, which are involved in short-term integration, such as the fusiform face area, and the parahippocampal place area. This research permits investigating changes related to areas activated during learning in the brain, as it shows that there are brain areas that differ in integrating past learning experiences by either calculating long-term outcome predictions or instantaneous reinforcement expectancies (Glascher, & Buchel, 2005).

The second article about brain research and learning is titled Brain Research, Learning, and Emotions: implications for education research, policy, and practice by Christina Hinton, Koji Miyamoto, and Bruno Della-Chiesa. The authors discuss implications for policy recommendations informed by brain research in the area of educational neuroscience. The first recommendation is to focus on the learning environment. The learning environment influences brain development greatly, and the authors propose a change in policy from focusing on the individual to focusing on restructuring the environment. The second recommendation entails making use of formative assessment. The brain is dynamic and constructed over time, and formative assessment is a powerful tool for guiding the development of abilities (Hinton, Miyamoto, & Della-Chiesa, 2008). The third recommendation is taking into account the importance of emotions. Emotion is essential to learning, and brain research suggests that schools should have positive learning environments that motivate students, and teachers should be trained in teaching students how to regulate their emotions, which is an important aspect of learning (Hinton, Miyamoto, & Della-Chiesa, 2008). The fourth is considering sensitive periods for language learning. Early foreign language instruction assists the brain in more efficiently and effectively learning its accent and grammar; starting instruction in pre-primary or primary school is advantageous (Hinton, Miyamoto, & Della-Chiesa, 2008). The fifth is informing reading instruction with neuroscience findings; a balanced approach to literacy informed by the dual importance of phonological and direct semantic processing in the brain is the most effective way to teach non-shallow alphabetic languages (Hinton, Miyamoto, & Della-Chiesa, 2008). The last is informing math instruction with neuroscience findings; because number and space are tightly linked in the brain, instructional methods that link these are powerful teaching tools (Hinton, Miyamoto, & Della-Chiesa, 2008).

The first article about information processing is titled Factors influencing the use of cognitive tools in web-based learning environments: A case study by Erol Ozcelik and Soner Yildirim. The authors found that students use Web-based cognitive tools for various cognitive tasks; cognitive tools have tremendous promise in empowering learners in Web-based learning environments (Ozcelik, & Yildirim, 2005). The authors have the following recommendations for designing and using cognitive tools for Web-based learning environments: 1) Provide an orientation for the tools that will be used; 2) the cognitive tools should be easy to use; 3) activities in instruction should demand using higher-order thinking; and, 4) internet connections should be more secure, stable, and fast (Ozcelik, & Yildirim, 2005).

The second article about information processing is titled Multimedia, Information Complexity and Cognitive Processing by Hayward P. Andres. The study shows a causal model of how multimedia and information complexity interact to influence sustained attention, mental effort and information processing quality, which all have an impact on comprehension and learner confidence and satisfaction outcomes (Andres, 2004). The results of the study show that “presentation media, or format, directly impacted sustained attention, mental effort, information processing quality, comprehension, learner confidence and satisfaction; information complexity had direct effects on sustained attention, mental effort, and information processing quality; and comprehension and learner confidence and satisfaction were influenced through a mediating sequence of sustained attention, mental effort, and information processing quality” (Andres, 2004).

The first article about problem-solving is titled The Relationship between Creative Cognition and Problem Solving by Serhat Arslan, Yunus Akdeniz, and Dilek Unal. The study’s aim is to search for the relationship between problem solving and creative cognition, and the results show that problem solving is positively related to creative cognition (Arslan, Akdeniz, & Unal, 2016).

The second article about problem-solving it titled Problem Solving as an Encoding Task: A Special Case of the Generation Effect by Jasmin M. Kizilirmak, Berit Wiegemann, and Alan Richardson-Klavehn. The authors found that the generation effect for CRAT, in which a new solution has to constructed based on existing knowledge rather than retrieving the solution from existing knowledge, shows a distinctive pattern of memory performance depending on the type of test, for example, solving old items, or indirect test, versus recognizing old items or solutions, or direct test (Kizilirmak, Wiegemann, & Richardson-Klavehn, 2016).

 

References

Andres, H. P. (2004). Multimedia, information complexity and cognitive processing. Information

            Resources Management Journal, 17(1), pp. 63-78. Retrieved from

http://search.proquest.com.ezp.waldenulibrary.org/central/docview/215883684/90C4A635D6EB4AEDPQ/11?accountid=14872

Arslan, S., Akdeniz, Y., & Unal, D. (2016). The relationship between creative cognition and

problem solving. Multidisciplinary Academic Conference. Retrieved from

http://web.a.ebscohost.com.ezp.waldenulibrary.org/ehost/detail/detail?sid=06f7468d-8523-4d36-9fff-473e0aca641b%40sessionmgr4010&vid=0&hid=4209&bdata=JnNpdGU9ZWhvc3QtbGl2ZSZzY29wZT1zaXRl#AN=117451963&db=a9h

Glascher, J., & Buchel, C. (2005). Formal learning theory dissociates brain regions with different

temporal integration. Neuron, 47, pp. 295-306. Retrieved from       http://search.proquest.com.ezp.waldenulibrary.org/central/docview/1503653277/7F242C86BBBF4214PQ/10?accountid=14872

Hinton, C., Miyamoto, K., & Della-Chiesa, B. (2008). Brain research, learning and emotions: implications for education research, policy, and practice. European Journal of Education,  43(1). Retrieved from http://web.a.ebscohost.com.ezp.waldenulibrary.org/ehost/detail/detail?sid=9b4fcc46-4395-4c69-8a52-4d276a9f7385%40sessionmgr4009&vid=0&hid=4209&bdata=JnNpdGU9ZWhvc3QtbGl2ZSZzY29wZT1zaXRl#AN=28714643&db=a9h

Kizilirmak, J. M., Wiegemann, B., & Richardson-Klavehn, A. (2016). Problem solving as an  encoding task: A special case of the generation effect. Journal of Problem Solving, 9. Retrieved from http://web.a.ebscohost.com.ezp.waldenulibrary.org/ehost/detail/detail?sid=91e45c5a-d0f2-4f0b-9443-1d8c68efb7ea%40sessionmgr4008&vid=0&hid=4209&bdata=JnNpdGU9ZWhvc3QtbGl2ZSZzY29wZT1zaXRl#AN=116531370&db=a9h

Ozcelik, E., & Yildirim, S. (2005). Factors influencing the use of cognitive tools in Web-based learning environments: A case study. The Quarterly Review of Distance Education, 6(4), 295-308. Retrieved from http://web.b.ebscohost.com.ezp.waldenulibrary.org/ehost/detail/detail?sid=d9b335ad-b28c-478b-958d-d43233065d05%40sessionmgr105&vid=0&hid=118&bdata=JnNpdGU9ZWhvc3QtbGl2ZSZzY29wZT1zaXRl#AN=19580578&db=a9h

 

Education · Instructional design

Fitting The Pieces Together

fitting-together

For this week’s assignment, I am going to fit the pieces together by combining what I have learned throughout the course to assess my own learning.

Fitting the Pieces Together

Now that you have a deeper understanding of the different learning theories and learning styles, how has your view on how you learn changed?

The most important that I have noticed about how I learn, and that I think has also had an effect on the way I learn is reading about how the strategies that I use for learning are considered to be of low utility. For example, the strategies that I have always used are highlighting/underlining, and rereading. However, as stated in Dunlosky, Rawson, Marsh, Nathan, & Willingham (2013), highlighting does not do much to increase performance on tasks requiring making inferences. Rereading, on the other hand, is also stated by Dunlosky et al. (2013) as low utility, but the authors do mention some benefits of this strategy, such as having benefits across a wide array of text materials, appearing to have durable effects across delays when rereading is spaced, and being effective for recall-based measures of memory.

What have you learned about the various learning theories and learning styles over the past weeks that can further explain your own personal learning preferences?

            I am going to apply some effective techniques from now on, for example, elaboration, and comprehension monitoring (Ormrod, n.d., Laureate education). I think that these techniques will help me with remembering, which is an area that I am having problems with. I think that after reading Dunlosky et al. (2013), my memory issues can be explained through the faulty use of learning strategies. Regarding learning styles, I still believe that I am more of a visual learner. In terms of multiple intelligences (Armstrong, 2009), I believe that I have more capabilities in certain areas than in others, for example, in linguistic intelligence, logical-mathematical intelligence, and intrapersonal intelligence. The linguistic intelligence can explain my affinity for writing; the logical-mathematical intelligence might explain my thinking patterns in categorizing, classifying, inferencing, and generalizing; and, the intrapersonal intelligence can explain how my self-knowledge has led me to understand that I have to use other learning strategies to assist me in remembering better, to be aware of my moods and how they affect my learning, and to have self-discipline, which has helped me learn well in an online, self-directed environment. In regard to learning theories, after completing the learning matrix and mind map assignments, I have seen how networks of learning are very important, as shown in connectivism, and how we are actually involved in social interactions, even in our online learning communities, and environment.

What role does technology play in your learning (i.e., as a way to search for information, to record information, to create, etc.)?

            After reading about Web 2.0 tools for our mind map assignment, I realized that I use technology for searching, remembering, creating, and sharing what I learn. For example, for searching I use Google; for remembering, I use my calendar online and on my phone, Cortana (assistant similar to Siri), and bookmarking; for creating, I use Microsoft office tools, Wix for website creation, and Teachable for course creation; and for sharing, I use my social networking sites such as Facebook and Instagram, LinkedIn, blogs, chats, Skype, and my personal networks.

 

References

Armstrong, T. (2009). Multiple intelligences in the classroom (3rd ed.). Alexandria, VA:

Association for Supervision and Curriculum Development.

Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving

Students’ Learning with Effective Learning Techniques: Promising Directions from

Cognitive and Educational Psychology. Psychological Science in the Public Interest, 14(1),

4-58. doi:10.1177/1529100612453266

 

 

Education · Instructional design

Connectivism: My Reflection Post.

connectivism_image_png_opt283x212o00s283x212

My network has changed the way I learn considerably. For example, when I was younger, we did not have the Internet yet. I learned the traditional way by reading only books, and my personal network. In my teens, the Internet arrived on Aruba, and I had the slow connection via the phone. Any time someone lifted the phone, the connection would be lost, and I had to start all over again. This caused an interruption when I was looking for information to learn. When I went to the United States to study in 2001, I experienced a fast, and wireless, connection, and it was at this time that learning became faster and more convenient for me. I could search for new information in an efficient manner that took less time. For me, the social networking site, especially Facebook, has helped me learn from others through discussions about different topics, including the groups that I am a member of which discuss specific topics. The Web 2.0 tools are mostly new to me, specifically the RSS feed, Teachable, WordPress, Google docs, and Grammarly. I did not have any previous knowledge of, or experience with, these educational tools. They help me share my own opinions and knowledge, write better, and learn from others. The Web 3.0 tool that I use is Cortana, which is an assistant, similar to Siri from Apple. Cortana knows all my preferences for different issues, and it keeps all of my information handy for me in one place, sends me reminders about things I have on my calendar, and keeps me organized. Via blogs, I learn about the topics that I am interested in in a concise way.

The digital tools that best facilitate learning for me are using the internet to search for information, watching videos, reading blogs, and using the online library, and Blackboard from Walden University.

In order to gain new knowledge, I tend to search via Google, search the online library, or download books on my Barnes and Noble Nook app. I also ask people whom I believe have knowledge about the new information I am seeking.

My personal learning network supports the central tenets of connectivism in that my learning occurs through a ‘distribution within a network, it is social, technologically enhanced, and the network is diverse’ (Davis, Edmunds, & Kelly-Bateman, 2008).

 

Reference

Davis, C., Edmunds, E., & Kelly-Bateman, V. (2008). Connectivism. In M. Orey (Ed.),

            Emerging perspectives learning, teaching, and technology. Retrieved from

http://epltt.coe.uga.edu/index.php?title=Connectivism

 

Education · Instructional design

Connectivism

 

In Connectivism, learning occurs through knowledge distribution within a network; it is social; it is enhanced through the use of technology; and it entails recognizing and interpreting patterns (Davis, Edmunds, & Kelly-Bateman, 2008).

This mind map represents my network connections, including social networking sites and apps, personal learning networks, Web 2.0, Web 3.0, virtual world, and blogs.

 

my-network-connections

 

Reference

Davis, C., Edmunds, E., & Kelly-Bateman, V. (2008). Connectivism. In M. Orey (Ed.),

Emerging perspectives on learning, teaching, and technology. Retrieved from

http://epltt.coe.uga.edu/index.php?title=Connectivism

Education · Instructional design · Uncategorized

Evaluating and Identifying Online Resources

brain1-mantle

 

The second week of the Learning Theories and Instruction course covered the topics of the brain and learning, how the brain processes information, and how we solve problems.

For the second assignment, I am going to comment on some very interesting academic journal articles about brain research and learning, information processing in the brain, and problem-solving. I will discuss two articles for each of the three topics.

The first article about brain research and learning is titled Formal Learning Theory Dissociates Brain Regions with Different Temporal Integration by Jan Glascher and Christian Buchel. The researchers created an experiment using fMRI (Functional magnetic resonance imaging) to study Pavlovian fear conditioning where reinforcement incidents were fully varied during the experimental course. The researchers used the formal learning theory (Rescorla-Wagner model) as their theoretical framework. Using the fMRI and this theoretical perspective, they found that learning-related brain regions, such as the amygdala, which is involved in long temporal integration, and the higher perceptual regions, which are involved in short-term integration, such as the fusiform face area, and the parahippocampal place area. This research permits investigating changes related to areas activated during learning in the brain, as it shows that there are brain areas that differ in integrating past learning experiences by either calculating long-term outcome predictions or instantaneous reinforcement expectancies (Glascher, & Buchel, 2005).

The second article about brain research and learning is titled Brain Research, Learning, and Emotions: implications for education research, policy, and practice by Christina Hinton, Koji Miyamoto, and Bruno Della-Chiesa. The authors discuss implications for policy recommendations informed by brain research in the area of educational neuroscience. The first recommendation is to focus on the learning environment. The learning environment influences brain development greatly, and the authors propose a change in policy from focusing on the individual to focusing on restructuring the environment. The second recommendation entails making use of formative assessment. The brain is dynamic and constructed over time, and formative assessment is a powerful tool for guiding the development of abilities (Hinton, Miyamoto, & Della-Chiesa, 2008). The third recommendation is taking into account the importance of emotions. Emotion is essential to learning, and brain research suggests that schools should have positive learning environments that motivate students, and teachers should be trained in teaching students how to regulate their emotions, which is an important aspect of learning (Hinton, Miyamoto, & Della-Chiesa, 2008). The fourth is considering sensitive periods for language learning. Early foreign language instruction assists the brain in more efficiently and effectively learning its accent and grammar; starting instruction in pre-primary or primary school is advantageous (Hinton, Miyamoto, & Della-Chiesa, 2008). The fifth is informing reading instruction with neuroscience findings; a balanced approach to literacy informed by the dual importance of phonological and direct semantic processing in the brain is the most effective way to teach non-shallow alphabetic languages (Hinton, Miyamoto, & Della-Chiesa, 2008). The last is informing math instruction with neuroscience findings; because number and space are tightly linked in the brain, instructional methods that link these are powerful teaching tools (Hinton, Miyamoto, & Della-Chiesa, 2008).

The first article about information processing is titled Factors influencing the use of cognitive tools in web-based learning environments: A case study by Erol Ozcelik and Soner Yildirim. The authors found that students use Web-based cognitive tools for various cognitive tasks; cognitive tools have tremendous promise in empowering learners in Web-based learning environments (Ozcelik, & Yildirim, 2005). The authors have the following recommendations for designing and using cognitive tools for Web-based learning environments: 1) Provide an orientation for the tools that will be used; 2) the cognitive tools should be easy to use; 3) activities in instruction should demand using higher-order thinking; and, 4) internet connections should be more secure, stable, and fast (Ozcelik, & Yildirim, 2005).

The second article about information processing is titled Multimedia, Information Complexity and Cognitive Processing by Hayward P. Andres. The study shows a causal model of how multimedia and information complexity interact to influence sustained attention, mental effort and information processing quality, which all have an impact on comprehension and learner confidence and satisfaction outcomes (Andres, 2004). The results of the study show that “presentation media, or format, directly impacted sustained attention, mental effort, information processing quality, comprehension, learner confidence and satisfaction; information complexity had direct effects on sustained attention, mental effort, and information processing quality; and comprehension and learner confidence and satisfaction were influenced through a mediating sequence of sustained attention, mental effort, and information processing quality” (Andres, 2004).

The first article about problem-solving is titled The Relationship between Creative Cognition and Problem Solving by Serhat Arslan, Yunus Akdeniz, and Dilek Unal. The study’s aim is to search for the relationship between problem solving and creative cognition, and the results show that problem solving is positively related to creative cognition (Arslan, Akdeniz, & Unal, 2016).

The second article about problem-solving is titled Problem Solving as an Encoding Task: A Special Case of the Generation Effect by Jasmin M. Kizilirmak, Berit Wiegemann, and Alan Richardson-Klavehn. The authors found that the generation effect for CRAT, in which a new solution has to constructed based on existing knowledge rather than retrieving the solution from existing knowledge, shows a distinctive pattern of memory performance depending on the type of test, for example, solving old items, or indirect test, versus recognizing old items or solutions, or direct test (Kizilirmak, Wiegemann, & Richardson-Klavehn, 2016).

 

References

Andres, H. P. (2004). Multimedia, information complexity and cognitive processing. Information  Resources Management Journal, 17(1), pp. 63-78. Retrieved from http://search.proquest.com.ezp.waldenulibrary.org/central/docview/215883684/90C4A635D6EB4AEDPQ/11?accountid=14872

Arslan, S., Akdeniz, Y., & Unal, D. (2016). The relationship between creative cognition and  problem solving. Multidisciplinary Academic Conference. Retrieved from http://web.a.ebscohost.com.ezp.waldenulibrary.org/ehost/detail/detail?sid=06f7468d-8523-4d36-9fff-473e0aca641b%40sessionmgr4010&vid=0&hid=4209&bdata=JnNpdGU9ZWhvc3QtbGl2ZSZzY29wZT1zaXRl#AN=117451963&db=a9h

Glascher, J., & Buchel, C. (2005). Formal learning theory dissociates brain regions with different temporal integration. Neuron, 47, pp. 295-306. Retrieved from       http://search.proquest.com.ezp.waldenulibrary.org/central/docview/1503653277/7F242C86BBBF4214PQ/10?accountid=14872

Hinton, C., Miyamoto, K., & Della-Chiesa, B. (2008). Brain research, learning and emotions: implications for education research, policy, and practice. European Journal of Education, 43(1). Retrieved from http://web.a.ebscohost.com.ezp.waldenulibrary.org/ehost/detail/detail?sid=9b4fcc46-4395-4c69-8a52-4d276a9f7385%40sessionmgr4009&vid=0&hid=4209&bdata=JnNpdGU9ZWhvc3QtbGl2ZSZzY29wZT1zaXRl#AN=28714643&db=a9h

Kizilirmak, J. M., Wiegemann, B., & Richardson-Klavehn, A. (2016). Problem solving as an  encoding task: A special case of the generation effect. Journal of Problem Solving, 9. Retrieved from http://web.a.ebscohost.com.ezp.waldenulibrary.org/ehost/detail/detail?sid=91e45c5a-d0f2-4f0b-9443-1d8c68efb7ea%40sessionmgr4008&vid=0&hid=4209&bdata=JnNpdGU9ZWhvc3QtbGl2ZSZzY29wZT1zaXRl#AN=116531370&db=a9h

Ozcelik, E., & Yildirim, S. (2005). Factors influencing the use of cognitive tools in Web-based learning environments: A case study. The Quarterly Review of Distance Education, 6(4), 295-308. Retrieved from http://web.b.ebscohost.com.ezp.waldenulibrary.org/ehost/detail/detail?sid=d9b335ad-b28c-478b-958d-d43233065d05%40sessionmgr105&vid=0&hid=118&bdata=JnNpdGU9ZWhvc3QtbGl2ZSZzY29wZT1zaXRl#AN=19580578&db=a9h