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Impact of Digital Learning on Poverty and/or Digital Divide and/or Access to Technology

Impact of Digital Learning on poverty and Digital Divide

Some insight is given first on the meaning of the terminologies used in the topic tittle followed by the bulleted list of impacts with relevant explanations.

Digital Learning encompasses a broad range of educational practices that utilizes digital technologies to facilitate learning. It includes various modes of delivery such as:

Online Learning – A form of distance education where the primary delivery mechanism is via the internet.

Blended Learning – This combines both online and face-to-face teaching.

Hybrid Learning – Similar to blended learning, but often involves a more significant redesign of the learning experience. Students do the majority of their learning online, coming to campus only for specific face-to-face activities that cannot be done satisfactorily online.

HyFlex Learning – This model gives student the choice of how they participate in the course, whether online or in-person, and allows them to switch between modes as needed.

Open learning – This includes open educational resources (OER) like open text books, which are freely accessible and can be downloaded by students and instructors.

MOOCs (Massive Open Online Courses) – These are fully open courses available online to any one, and often for free.

Flexible learning – This approach provides student with more choices regarding when, where and how they learn.

Digital learning can be defined simply as: “learning that is supported by Technology.”

Walker, Mark. (2024)

Poverty is defined as the state or condition were people or communities cannot meet a minimum standard of living because they lack the proper resources. These include (but are not limited to) financial resources, basic healthcare and education clean drinking water and infrastructure (poverty, n.d.)

Digital divide is a term that refers to the gap between demographics and regions that have access to modern Information and Communication Technology (ICT), and those that don’t or have restricted access. This technology can include the Telephone, television, personal computers and Internet connectivity. (digital-divide, n.d.)

Digital learning has significant impact on both poverty and the digital divide, with various positive and negative implications:

POSITIVE IMPACT:

§  Increased access to education:

Digital learning provides educational opportunities to individuals in remote or underserved areas where traditional educational infrastructure is lacking. This helps in bridging the educational gap between urban and rural areas.

A developing country can draw on teachers with superior knowledge from advanced countries rather than local teachers who first have to learn the requisite skills before they can train others. Khan, H. & Williams, J. (2006).

§  Flexibility and Convenience:

Digital learning offers flexibility, allowing students to learn at their own pace and on their own schedule. This can be particularly beneficial for working adults or those with family responsibilities.

§  Cost-effective education

Digital learning reduces the cost associated with traditional education, such as transportation, housing, and physical text books. Open educational resources (OER) and MOOCs (Massive Open Online Courses) provides free or low cost learning materials.

§  Skill Development:

Digital learning platforms often offers courses in high demand skills, such as coding, digital marketing and data analysis, which improves employability and potentially lift individuals out of poverty.

NEGATIVE IMPACT:

§  Access Inequality:

Not everyone has equal access to the necessary technology and internet connectivity required for digital learning. This is particularly true for low income families and those in rural or remote areas, exacerbating the digital divide.

§  Quality of Learning:

The quality of digital learning can vary significantly. Student from Wealthier backgrounds may have access to better resources, such as high quality devices and faster internet, as well as more support from parents and tutors.

§  Digital Literacy:

Effective participation in digital learning requires a certain level of digital literacy. Those who lack these skills, often from poorer backgrounds, may struggle to benefit fully from online education.

§  Support systems:

Student from low income families may lack the necessary support systems at home, such as quite place to study or parental guidance, which can hinder their ability to succeed in a digital learning environment.

MITIGATION STRATEGIES:

§  Government and Institutional Support:

Government and educational institutions can provide subsidies or loans for digital devices and internet access for low income families. They can also invest in public Wi-Fi hot spots and community centers with internet access.

§  Teacher Training:

Training teachers to effectively use digital tools and platforms can improve the quality of Online education and ensure that all student receive a high standard of education.

§  Digital Literacy Programs

Implementing digital literacy programs can help equip student and their families with the necessary skills to navigate and benefit from digital learning platforms.

§  Policy Interventions:

Policies aimed at reducing poverty, such as improving economic opportunities and social services, can indirectly improve access to digital learning by addressing the root cause of the digital divide.

In conclusion, while digital learning has the potential to reduce educational inequalities and provide opportunities for those in poverty, it also risks exacerbating existing disparities if not carefully managed. Ensuring equitable access to technology and support systems is crucial for maximizing the benefit of digital learning for all.

“Controlled Access: How China’s Internet Policies Shape Learning”

How China’s Communist Party policies affect the digital learning landscape in China.

Positive and Negative Points about China’s Online Infrastructure

How China’s Policies Affect Student Learning and Education in China

The Chinese government has made efforts to build a nationwide digital learning system with abundant open resources to promote education equity. This initiative has been met with both positive and negative features when related to the learning quality for Chinese students. It is evident that a more constructive learning outcome is associated with better DLE equipment and network conditions, which positively affects learning performance in students. This also highlights evident negative features which denote that positive learning performance is linked to economic conditions.

Positive: The CPC has emphasized online education in the 19th National Congress report, which demonstrates major development. China has demonstrated that it is focused on building basic infrastructure for online education, which has been referred to as the implementation of the “Modern Distance Education Project.” Development of the National K-12 Education Resource Network.

Positive: When the iPhone was introduced in 2007 it greatly accelerated Internet access across China. It was this adoption of mobile Internet which led to a significant increase in online education; shifting it from a supplementary role to a key pillar of Chinese education.

Positive: The “Double Reduction” policy was brought in to reduce homework and significantly eliminate off-campus training burdens. Also included were measures to standardize and regulate online education.

Positive: China has gone through four stages in the development of online education policies, and the future of online education in China looks promising due to the existing polices and different measures to promote lifelong learning and education for all.

Negative: Despite the rapid development of online education, challenges remain. Some issues within the development of online education are the digital divide, supervision of the teaching process, and cooperation with the enterprise, which needs more comprehensive initiatives for further improvement.

Negative: Some of the concerns which are associated with the topic include “false propaganda” and “price gouging” by some institutions that offer education.

Positive: In the last few years, there is an increase in the use of online education in the rural areas.

The Online Learning Survey conducted by the Big Data Center of the Graduate School of Education, Peking University, showed that China’s policy was indeed supportive of digital education. It determined the following: The findings of the study revealed that family income, parents’ education level, and professional status influenced online learning among students in China.

Positive: During Covid 19 the Chinese Ministry of Education mandated a nationwide shift to online learning to maintain educational continuity during the pandemic.

Negative: 18.4% of students reported inadequate equipment. 37.3% faced network issues. 46.95% of high school students reported a decrease in overall learning scores.

Positive: Governments and schools provided free access to extensive online learning materials and platforms like Zoom and Tencent Classroom.

Negative: However, some challenges were observed during the implementation of the program, including network congestion, poor quality of hardware, and limited interactions between the teachers and students. As a result, students who had access to better resources at home were able to use online resources to their advantage, which could have further amplified the existing disparities in learning outcomes between students from different backgrounds.

Positive: Over 200 million students participated in online classes as part of the official curriculum from February to August 2020.

Negative: There was a significant positive relationship between student success and equipment and internet quality. The students from the low economic class experienced more challenges. These challenges affected the quality and efficiency of online teaching negatively. Furthermore, these problems revealed the existing digital divide in China, which did not disappear during the pandemic and affected the fairness of online learning.

It is evident that China’s Communist Party policies in the field of digital learning are diverse and can be observed in both positive and negative aspects. The government’s long-term commitment to the implementation of a comprehensive digital learning system has greatly enhanced educational equality and student inclusion throughout the country. Measures such as the “Modern Distance Education Project” and the “Double Reduction” policy show a clear willingness to build online education facilities, decrease homework pressure, and regulate online education.

There are positive aspects inherent in China’s digital initiative such as strengths of China’s web infrastructure which include the fast growth of primary infrastructure, the extensive utilization of a mobile web (after the advent of iPhone), and the large-scale application of online education in rural regions. Such advancements have made it possible to have a sound online education system. Moreover this is evident with the government’s preparedness during the COVID 19 outbreak where over 200 million students were taking their classes online and there was a wide range of free online learning resources available.

Nevertheless, these advancements come with significant challenges. The issue of digital divide persists, as the quality of equipment and the access to the internet differ, leading to the creation of different learning environments. Chinese family income and parents’ education level heavily determine the online learning experience of students, thus exacerbating the disparities in the education sector. Other challenges such as network congestion, lack of hardware, and limited face-to-face interaction between teachers and students also contribute to these problems.

Sources

Guo C, Wan B. The digital divide in online learning in China during the COVID-19 pandemic. Technol Soc. 2022 Nov;71:102122. doi: 10.1016/j.techsoc.2022.102122. Epub 2022 Sep 13. PMID: 36118102; PMCID: PMC9468296. 

Jiang, Y., Shang, J., & Jiao, L. (2023). Review of China’s Online Education Policy, 1999–2022. ECNU Review of Education, 6(1), 155-182. https://doi.org/10.1177/20965311221099581

Walker, M.D. What is Digital Learning? In: Digital Learning. How modern technology is Changing education. Sicklebrook publishing, Sheffield U.K.,2024

Khan, Habibullah & Williams, Jeremy. (2006). Poverty Alleviation Through Access to Education: Can E-Learning Deliver?. SSRN Electronic Journal. 10.2139/ssrn.1606102.

Poverty. (n.d.). Investopedia. Retrieved May 25, 2024 from https://www.investopedia.com/terms/p/poverty.asp

 Digital-divide. (n.d.) techtarget. Retrieved May 25, 2024 from https://www.techtarget.com/whatis/definition/digital-divide

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IMPACT OF GROUPS, NETs, SETs, COMMUNITIES AND COLLECTIVES ON MY PLAN FOR THE CREATION OF MY DIGITAL PRESENCE AND DIGITAL IDENTITY

Social learning processes particularly, the one that involves the use of digital platforms (social media platforms or educational social software), leads to the existence or emergence of social forms for learning or in other words social learning structures namely: Groups, Nets, Sets and collectives. The three of those namely: Group, Nets and Sets, are specifically referred to as the three kinds of aggregation of Learners in either formal or informal learning.

Groups are social forms where individual deliberately join others with shared goals and identity with group norms and behaviors.

Nets are social forms where the connections between individuals and sometimes clusters of individuals are what binds them together.

Sets are social forms where people may have no knowledge of others in the set but are clustered by commonalities between them. (Dron, J, & Anderson, T. 2014))

Since the creation of my digital presence and digital identity requires such consideration as what kind of things do I post online, what not to post and how I wish others would perceive me online, then I will always have to consider the how my online engagement will affect Groups, Nets, Sets, communities and collectives which will be accessing my online content. Thus, I will have to make sure the content I post online remain relevant all the social forms of learners. The development approach and presentation of my content posted online will be tailored to suit the various audiences namely groups, Net, Sets, communities and collectives. In this proceeding, eventually the scope and quality of Digital Identity and Digital presence plan (DIDP) will be impacted.

Reference

Dron, J, & Anderson, T. (2014). Teaching Crowds. Athabasca University Press. (Note: free PDF available for download). Chapter 4 – 7.

Stewart, B., Phipps, L., & Cormier, D. (2019, April 10). The Participatory open: Can we build a Pro-Social, Pro-Societal web? [Video]. You Tube. https://oer19.oerconf.org/sessions/the-participatory-open-can-we-build-a-pro-social-pro-societal-web-o-127/ 

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VISUAL NETWORK MAPPING

The Visual Network Mapping has been prepared using: https://app.diagrams.net/

DESCRIPTION ON THE VISUAL NETWORK MAP.

The visual network Map above shows and represent my social network map and my position within the network. The nodes represent the different entities that I am related to in my social networks. The “Me” node represent myself positioned within the structure of my social network. The other entities, which I am related to namely are: Personal friends, Academic community (MALAT), Higher learning institutions, Work organization, Business partners, Family members, Charity organizations and religious institutions

The nodes that are related to me, some of them are also related to each other. My business partners some of them are related to me as my workmates. My family member is related to me as a business partner. My personal friends connect with me through the same religious institution. My schoolmates are also my friends.

Now if you analyze the network map wholistically with all the nodes and relations between them in terms of centrality, you will find that the “Me” node provides for all the three types of centralities namely Degree, Betweenness and closeness centrality.

Degree centrality: Is used to identify the most connected node in the network. Betweenness centrality identifies the “brokers” or gate keeper” in the network these nodes have a unique position where they connect different parts of the network, facilitating or controlling the flow of information. Closeness centrality measures how quickly a node can reach every other node in the network via the shortest paths. In a coalition, these nodes can disseminate information or exert influence quickly due to their close proximity to all other nodes.

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DIGITAL IDENTITY AND DIGITAL PRESENCE PLAN

The use of digital platforms now makes it a necessity that one must consider issues related to individuals’ digital identity and digital presence. In academic realms, the need for consideration on individual digital identity and digital presence becomes even more important.

It is very common nowadays you find an individual using more than one digital platforms (e.g: Facebook, Twitter, LinkedIn, etc ) for varied purposes academic and nonacademic. All along these varied purposes of using all these digital platforms one must keep in mind these fundamental questions: What kind of things do you tend to post online and how much thought do you give to choose or creating them? What would you not post? What mental processes do you go through in deciding what to post, when and how? Do you have a different personality, presentation or persona on different sites or services? If so, why, and how do they differ? How do you think you are perceived online? Why? Schryver, K. (2013, February 5)

Critical questions like: How do you wish others would perceive you online? How do you worry you might actually come across? Makes it relevant now for one having a Digital Identity and Digital Presence (DIDP) Plan. In this regard my DIDP plan will be set intentionally to support the cultivation of my digital Identity and Digital Presence throughout the DIpLAT program.

THE GOAL AND PURPOSE OF MY DIDP PLAN

SPECIFYING AND DEFINING THE SCOPE OF MY DIGITAL ENGAGEMENT FOR ACADEMIC AND NONACADEMIC PURPOSES WITHIN THE TIMEFRAME OF MY ACADEMIC PROGRAM.

APPROACH FOR ACHIEVING THE GOAL

Regular use of My Blog site to post relevant content related to my program of study. Commenting on the blogs of my other fellow students. Posting relevant videos related to my program of study on my youtube channel and post those links to my blog.

I will maintain a true identity of Myself on all social network platforms and will be cautious on what I post as those content may remain in those platforms for many years to come.

SKILLS AND KNOWLEDGE GAP

I will continue refining my knowledge on the use of any specific social network platform and will pay special attention on the privacy and security features of any social media platform since security vulnerabilities are always in existence on these social media (digital) platforms.

ADDRESSING KNOWLEDGE GAP:

Make us of web-based research and Learning tools continuously over the entire period of my academic program.

MEASURE OF SUCCESS:

Having at least a monthly web engagement activity on at least one or more of any of the digital platforms namely Web blog, youtube, Twitter, LinkedIn, |slack

Reference:

KELLY SCHRYVER. (February 5, 2013 Tuesday). Guest Post | Who Are You Online? Considering Issues of Web Identity. The New York Times Blogs (The Learning Network). https://advance.lexis.com/api/document?collection=news&id=urn:contentItem:57NS-B791-DY2M-W4PJ-00000-00&context=1516831.

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MY THOUGHTS

The Alternative tension pair presented by Dave, introduces new considerations. It attempts to check if what we consider to be our web engagements are they truly digital and professional? Essentially, this can be a very tricky question as sometimes the dividing line is very thin between what one would consider to be digital activity and the other, which is not a digital activity. |So literally speaking, Daves consideration should be taken into account before progressing into the Mapping activity.

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SYMPOSIUM-ACADEMIC REFLECTION

At the very beginning of the MALAT and DipLAT programs, Symposium has been an eye opener on the enormous possibilities in the use of educational technologies. In all the live recordings I have managed to attend and those pre-recorded videos I have watched, my key interest would be in the broader use of AI in educational activities such as instructional design and knowledge management systems in general.

I was interested in the idea of using disruptive, innovative and emerging technologies (DIET) to facilitate knowledge transfer. I think with the imminent reality of the huge retirement of the skilled and highly knowledgeable labor force as suggested by Corie Houldsworth ( Houdsworth, 2024) knowledge transfer is an urgent requirement. The DIET tools may include generative AI.

As a finding, “creating communities of practice” by Curie (Houldsworth, 2024 captured my interest as well. I would think this goes hand in hand with the other finding: “Increasing users’ literacy” by curie (Houldsworth,2024). User literacy also increases the technology adoption and hence facilitate knowledge transfer.

I was intrigued by the idea of Digital twins, which is a virtual representation of whatever you have implemented as defined by Curie (Houldsworth, 2024). The whole idea here is the digital “twins” would save as a fully functional model of a live implementation. With the “digital twins” users and experts alike can simulate or experiment various possibilities without worrying disrupting any live system. The negative side is that implementing “digital twins” is very expensive. However, for the purpose of knowledge transfer digital twins are still a worthwhile investment. I was further intrigued by the concept of “elevator pitch” as pointed out by Curie (Houldsworth, 2024) in her presentation. It is actually important to make use of appropriate platforms to publicize the outcome of any research work for it to be known and become usable.

I asked Curie during the presentation about the reliability of AI. She was cautious that it is still not very reliable and emphasized that the deployment should be taken carefully and progressively. In Fact, I agree with her AI is still not very reliable for its use to be done freely especially in nuclear industry endeavors and the medical field (Gherhes, 2018) Any such initiatives must be carefully supervised and seriously regulated. I am in agreement with Curie that the government and other international institutions alike should not be too restrictive in the adoption of collaborative platforms as the platforms will foster easy knowledge transfer.

I was surprised by the extent in which AI tools like ChatGpt has been so useful in the creation of open education resources. As presented by Jenny Heyman (Heyman, 2024). The reason for my surprise was basically how time efficient this whole process of creating open education material will be. On the contrary, what intrigued me though, even Jenny (Heyman, 2024) emphasized while answering my question that AI tools used for developing open education resources must be checked for quality assurance. Apparently, I am in agreement with Jenny (Heyman, 2024) as review of other literature attest to that (Gherhes 2018). For a foreseeable future , AI tools still will have significant contribution on the development of educational activities.

References:

Vasile Gherhes (2018, December). Why Are We Afraid of Artificial Intelligence (AI)?

https://www.researchgate.net/publication/330678764_Why_Are_We_Afraid_of_Artificial_Intelligence_Ai

Houldworth C. (2024, April 9). Human factors group and International work with the IAEA on communities of Priactice.

[Webinar].

Brewer, Heyman (2024 April 11). Using generative AI in Centres for Teaching and Learning- approaches, challenges, and opportunities

[Webinar].

[Image]. Businessman touching the brain of Artificial Intelligence (AI) Automation, Predictive analytics, Customer service AI-powered chatbot, analyze customer data, business and Technology.

Businessman Touching The Brain Working Of Artificial Intelligence Automation Predictive Analytics Customer Service Aipowered Chatbot Analyze Customer Data Business And Technology Stock Photo – Download Image Now – iStock (istockphoto.com)

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