Learning in a Digital Age

Learning in a Digital World

The congruent development of physical, intellectual, social, emotional, and spiritual faculties necessary to master life’s circumstances coupled with eclectic learning theories informs my philosophy of learning. I seek to prepare learners to achieve their fundamental skills, which are essential to manage their life with success. 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 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 (Downes, 2012; Siemens, 2008) learning theory and the way individuals learn
I had numerous educational experiences, both in an online and a face-to-face learning environment. The end of my second degree (MBA) in 1999 marked the end of my participation in a face-to-face learning environment. The traditional learning setting provided limited interactions with classmates, restricted access of information, fixated and hard information with books, library, and instructors as knowledge owners. In an online learning, information is volatile as the currency of information spurs new knowledge. The discussion forum with peers offers multifaceted information for knowledge creation, where instructors serve as facilitators. The advanced technology and Internet support current learning theories and deliver an auspicious milieu for blogs, wiki, and collaborative tools for an active and a dynamic learning experience in the digital world.
References
Driscoll, M. (2005). Psychology of Learning for Instruction. New York, NY: Allen & Bacon.
Layde, P. M., Christiansen, A. L., Peterson, D. J., Guse, C. E., Maurana, C. A., & Brandenburg, T. (2012). A model to translate evidence-based interventions into community practice. American Journal of Public Health, 102(4), 617-624. doi: 10.2105/AJPH.2011.300468.Shih, S.-C., Kuo, B.-C., & Liu, Y.-L. (2012).
Adaptively ubiquitous learning in campus math path. Educational Technology & Society, 15 (2), 298–308. Retrieved from http://content.ebscohost.com.ezp.waldenulibrary.org.

New Technologies in The Classroom

The New York City Department of Education (DOE) required teachers to use technology to enhance students’ learning. In 2008, at my former New York City High school in Brooklyn, where I taught mathematics, the assistant principal (AP) math equipped each math teacher with a laptop permitting instructors to revolutionize their professional preparation and use whiteboards  for instruction delivery. However, only two teachers out of seven were able to utilize the new technology.

Tired of using head projector and transparencies in the classroom, I subscribed to the use of interactive whiteboards, which seemed to be a new motivational tools for students. The effectiveness of the new technology in supporting teaching and learning (Maher, Phelps, Urane, & Lee, 2012) resided in students’ increased participation and performance in mathematics. Evidently, the resources such as the inclusion of interactive and simulation activities contributed to the increased student learning outcomes. Students were able to post module journals via their emails for discussion. I engaged my classes in jeopardy games every Friday, enabling students to review and remember math vocabulary and taught concepts. The first term scholarly report revealed an average of 90% of my students passing their math. Other five math teachers averaged less than 60%.

At the departmental review session with the school Principal and AP math, the five math teachers who have expressed low self-efficacy in experimenting with new technologies asked for professional development on using whiteboards in their classrooms. At the first departmental and professional development I related to how the application of Keller’s ARCS theory of attention, relevance, confidence, and satisfaction were important for students’ successful learning. I told them how the use of whiteboards enabled interactive and motivational activities that depicted real life problems for learners’ interest. Developing and boosting students’ self-efficacy was important for learner intrinsic motivation, while using whiteboard contributed to the external motivation for learning. The use of whiteboard supported YouTube videos
to end math class on taught concept and math games to emphasize presented skills.

Most of my students had problems with the abstract nature of mathematics. The use of whiteboard helped them comprehend the presented materials via a visualization, the core element for the modern educational model (Lakhvich, 2012). With whiteboards, I had access to animation software that assisted and facilitated my students’ comprehension of theoretical different topics
through visual-based acceptance (Lakhvich, 2012. An effective use an interactive assisted me getting and maintaining my students’ attention, improving relevancy, developing learners’ self-confidence and self-efficacy, and spawning pupils’ success and satisfaction (Driscoll, 2005). The digital resources assisted me compensate for gaps in my own skills (Bandura, 2002).
References
Bandura, A. (2002). Growing primacy of human agency in adaptation and change in the electronic era. European Psychologist, 7(1), 2-16. doi: 10.1027//1016-9040.7.1.2.
Driscoll, Marcy P.. Psychology of Learning for Instruction XML Vitalsource ebook for Laureate Education, 3rd Edition. Pearson Learning Solutions.
Lakhvich, T. (2012). Visualisation-assisted teaching: Can virtual give rise to real knowledge. Problems of Education in the 21st Century, 42, 5-7.
Maher, D., Phelps, R., Urane, N., & Lee, Mal. (2012). Primary school teachers' use of digital resources with interactive whiteboards: The Australian context. Australasian Journal of Educational Technology, 28(1), 138-158.

 

 

 

 

Connectivism

 

 

 

 

Figure 1.Connectivism MindMap

 

Connectivist’ principles consist of an academic structure to comprehend and appreciate learning. In connectivism, learners construct their knowledge through connective nodes (Siemens, 2006). As learners participate in a learning community, they collaborate, transact, act and reflect on information to generate and experience knowledge (Kop & Hill, 2008).

Impact of Connective Network

Naturally, the hierarchy acclimatizes static, structured, managed, and controlled knowledge to an institution or organization (Siemens, 2006). Schooled in the traditional education system up to the undergraduate level, this author constructed knowledge through archaic authoritative lecture and sources (books and physical libraries). He started using computers during his last year before he got his first degree in mathematics, due to his teaching assignment. The change of his educational environment contributed to his growth in using technology. During his second degree (MBA) in France, he learned to support his ideas through research, yet still through intricate knowledge. However, in his MS-IDT at Walden University, the writer learned to enjoy Web 2.0 and Web 3.0 tools to create, use, share, engage, and manage contents, relations, and applications. Indeed, the use of connective network empowers the organization to knowledge (Siemens, 2006).

In the Ph.D. program, in educational technology, this author has become an experienced user of connective network. He uses laptops and smartphones to access online and digital academic resources (books and library), researches on topical discussions and assignments. In the asynchronous learning environment, he interacts with classmates and instructors using learning management system (LMS) Blackboard Learn. He creates blogs, using Dreamweaver, uses really simple syndication (RSS) feeds to collect other blogs and interested links for information to stay current in his field. As self-regulated learner, this writer could say his network has changed the way he learned (Laureate Education, 2012).

Digital Tools

The Internet, blogs, Google docs, webinars, and cloud computing constitute some of the digital tools (Laureate Education, 2012) that facilitate this writer’s learning. He uses social network as diversions and interests. He also learns from his classmates and instructors from discussion posts and feedback.

Learning New Knowledge

            This author acquires new knowledge through class discussions and professors’ feedback.  He attends webinars, seminars and professional development, to update his skills. He learns from colleagues in the field of educational technology and subject matter experts (SMEs). He reads on dissertations of interest, peer-reviewed academic and professional journals, and conducts research in the library, using the Internet. The learner’s connectivism mindmap in figure 1 exemplifies the way he learns.

Reference

Kop, R., & Hill, A. (2008). Connectivism: Learning theory of the future or vestige of the past? International Review of Research in Open and Distance Learning, 9(3), 1–13.

Siemens, G. (2006). Knowing Knowledge. Retrieved from http://www.Lulu.com.

 

 

Cognitivism as a Learning Theory

 

Cognitivism is the study of the brain and the information processing. Bill Kerr, Stephen Downes, and Karl Kapp provide salient information on cognitivism and behaviorism. Learning theories (behaviorism, constructivism, cognitivism, and connectivism) similar to politics are full of isms. However, like other learning theories, these isms are not at variance with each other. Political beliefs might offer a common ground for individuals. Similarly, learning theories might provide joint field for educators. Thus, the author identifies steadiness or overlying foundations of learning theories, in the field of educational technology. Instructional designers might exemplify behaviorism, constructivism, cognitivism, and connectivism in their designs. While participants of political parties might resort to deceptive practices, theorists of an education system might refer to reliable options of use of theories.

Learning theories might guide educators in their choice for effective curriculum, for an instance. The answer to the problem is not to shift from one theory to another, but to select the suitable theory for effective profitability in a situation. Scholars need to be selective in their choice, to respond to the needs of the everchanging society, due to change in culture and technology. Neither behaviorism, nor constructivism, nor cognitivism provides 100% explanation of how individuals process information (Kapp, 2007).

According to Santrock (2009), the cognitive information processing involves first order thinking (computation, memorization, reading, and comprehension), "metacognition (monitoring progress and products of first order thinking), and transformative learning (reflecting on the limits of knowledge, the certainty of knowledge, and the criteria for knowing)" (p. 185). Thus, self-direction, metacognition, critical reflection, reflective discourse, and collaborative learning (Keegan, 2011; Stevens-Long, Schapiro, & McClintock, 2012) constitute key factors in online learning. Consequently, the continuing variability in individuals’ performance (Driscoll, 2005) and interaction in the global market, calls for Siemens’s (2006) theory of learning for the digital age (connectivism), which could provide a smarter approach to learning in the 21^st Century

 

References

Driscoll, M. (2005). Psychology of Learning for Instruction. New York, NY: Allen & Bacon.

Kapp, K. (2007, January 2). Out and about: Discussion on educational schools of thought [Web log post]. Retrieved from http://www.kaplaneduneering.com/kappnotes/index.php/2007/01/out-and-about-discussion-on-educational.

Keegan, P. (2011). Transformative e-learning and teaching in mandatory tertiary education. Asian Social Science, 7(11), 66-74. doi:10.5539/ass.v7n11p66.

Kerr, B. (2007, January 1). _isms as filter, not blinker [Web log post]. Retrieved from http://billkerr2.blogspot.com/2007/01/isms-as-filter-not-blinker.html.

Santrock, J. (2009). Introduction. In A topical approach to life-span development (pp. 3–41). New York, NY: McGraw-Hill.

Stevens-Long, J., Schapiro, S., & McClintock, C. (2012). Passionate scholars: Transformative learning in doctoral education. Adult Education Quarterly, 62(2), 180–198. doi: 10.1177/07417136.

 

 

 

 

 

 

The Purpose of Learning Theories in Educational Technology: The Way People Learn

Learning, a continuing exchange in societal and anthropological functioning, occurs in varieties of ways, as individuals interact with the biosphere (Driscoll, 2005).  People generally learned through books, news, and limited social interactions only. The Internet, development of the Web2.0, communication technologies, and social software provide new and interactive ways in which individuals learn. According to Siemens (2008) learning now occurs in a variety of ways. The theory of knowledge, which encompasses objectivism, pragmatism, and interpretivism forms the bases of behaviorism, cognitivism, and constructivism (Siemens, 2008); and inform the increased complexity of technology choices in the instructional design. The existing and emerging learning theories (http://www.learning-theories.com) advise learning transpire best in a community of learning or practice and personal networks (Tennyson, 2010).
Connectivism enables the learner to ascertain the objectivity and validity of the received information (knowledge) through the lens of knowledge experts, conduit, content, and context (Siemens, 2005). As individuals experience knowledge in time and space, through the various nodes in a network system, they gain new knowledge, become active cognitively, fortify and emancipate their minds. Apart from learning styles (http://www.learning-styles-online.com), most people subscribe to the continuous accretion method of learning (Siemens, 2005, p. 35). Technology facilitates and drives the ongoing process of learning and knowledge in the digital age.
References
Driscoll, M. P. (2005). Psychology of learning for instruction (3rd ed.). Boston, MA: Pearson Education.
Siemens, G. (2008, January 27). Learning and knowing in networks: Changing roles for educators and designers. Paper presented to ITFORUM. Retrieved from http://it.coe.uga.edu/itforum/Paper105/Siemens.pdf.
Tennyson, R. D. (2010). Historical reflection on learning theories and instructional design. Contemporary Educational Technology, 1(1). 1-17.