Misinformation and disinformation are rife, but so far it’s been seen as a challenge for policy-makers and big tech, including social media platforms.
The sheer volume of data being created makes it hard to tell what’s real and what’s not. From destroying 5G towers to conspiracies like QAnon and unfounded concern about election fraud, distrust is becoming the default – and this can have incredibly damaging effects on society.
So far, the tech sector – primarily social media companies, given that their platforms enable fake news to spread exponentially – have tried to implement some measures, with varying levels of success. For example, WhatsApp has placed a stricter limit on its message-forwarding capability and Twitter has begun to flag misleading posts.
the rise of tech startups that are exploring ways to detect and stem the flow of disinformation, such Right of Reply, Astroscreen and Logically.
Radianti, J., Majchrzak, T. A., Fromm, J., & Wohlgenannt, I. (2020). A systematic review of immersive virtual reality applications for higher education: Design elements, lessons learned, and research agenda. Computers & Education, 147, 103778. https://doi.org/10.1016/j.compedu.2019.103778
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2.2. Learning paradigms
An understanding of the existing learning paradigms is essential for performing an analysis of the current state of VR applications in higher education. Thus, we introduce the main ideas behind the existing learning paradigms. Literature distinguishes between behaviorism, cognitivism, and constructivism (Schunk, 2012). Other scholars also include experiential learning (Kolb & Kolb, 2012) to this list and, recently, connectivism has been introduced as a new learning paradigm (Kathleen Dunaway, 2011; Siemens, 2014). Each learning paradigm has developed various theories about educational goals and outcomes (Schunk, 2012). Each of these theories also offers a different perspective on the learning goals, motivational process, learning performance, transfer of knowledge process, the role of emotions, and implications for the teaching methods.
Behaviorism assumes that knowledge is a repertoire of behavioral responses to environmental stimuli (Shuell, 1986; Skinner, 1989). Thus, learning is considered to be a passive absorption of a predefined body of knowledge by the learner. According to this paradigm, learning requires repetition and learning motivation is extrinsic, involving positive and negative reinforcement. The teacher serves as a role model who transfers the correct behavioral response.
Cognitivism understands the acquisition of knowledge systems as actively constructed by learners based on pre-existing prior knowledge structures. Hence, the proponents of cognitivism view learning as an active, constructive, and goal-oriented process, which involves active assimilation and accommodation of new information to an existing body of knowledge. The learning motivation is intrinsic and learners should be capable of defining their own goals and motivating themselves to learn. Learning is supported by providing an environment that encourages discovery and assimilation or accommodation of knowledge (Shuell, 1986),RN23. Cognitivism views learning as more complex cognitive processes such as thinking, problem-solving, verbal information, concept formation, and information processing. It addresses the issues of how information is received, organized, stored, and retrieved by the mind. Knowledge acquisition is a mental activity consisting of internal coding and structuring by the learner. Digital media, including VR-based learning can strengthen cognitivist learning design (Dede, 2008). Cognitive strategies such as schematic organization, analogical reasoning, and algorithmic problem solving will fit learning tasks requiring an increased level of processing, e.g. classifications, rule or procedural executions (Ertmer & Newby, 1993) and be supported by digital media (Dede, 2008).
Constructivism posits that learning is an active, constructive process. Learners serve as information constructors who actively construct their subjective representations and comprehensions of reality. New information is linked to the prior knowledge of each learner and, thus, mental representations are subjective (Fosnot, 2013; Fosnot & Perry, 1996). Therefore, constructivists argue that the instructional learning design has to provide macro and micro support to assist the learners in constructing their knowledge and engaging them for meaningful learning. The macro support tools include related cases, information resources, cognitive tools, conversation, and collaboration tools, and social or contextual support. A micro strategy makes use of multimedia and principles such as the spatial contiguity principle, coherence principle, modality principle, and redundancy principle to strengthen the learning process. VR-based learning fits the constructivist learning design (Lee & Wong, 2008; Sharma, Agada, & Ruffin, 2013). Constructivist strategies such as situated learning, cognitive apprenticeships, and social negotiation are appropriate for learning tasks demanding high levels of processing, for instance, heuristic problem solving, personal selection, and monitoring of cognitive strategies (Ertmer & Newby, 1993).
Experientialism describes learning as following a cycle of experiential stages, from concrete experience, observation and reflection, and abstract conceptualization to testing concepts in new situations. Experientialism adopts the constructivist’s point of view to some extent—e.g., that learning should be drawn from a learner’s personal experience. The teacher takes on the role of a facilitator to motivate learners to address the various stages of the learning cycle (Kolb & Kolb, 2012).
Connectivism takes into account the digital-age by assuming that people process information by forming connections. This newly introduced paradigm suggests that people do not stop learning after completing their formal education. They continue to search for and gain knowledge outside of traditional education channels, such as job skills, networking, experience, and access to information, by making use of new technology tools (Siemens, 2014).
Ren, a former engineer with the People’s Liberation Army who went into consumer electronics, played the patriotic card, cautioning Jiang that ‘switching equipment technology was related to national security, and that a nation that did not have its own switching equipment was like one that lacked its own military’ (1). A quarter of a century later, other countries, led by the US, have belatedly grasped the wisdom of Ren’s remarks; the technology in question today is 5G
The company operates networks in 170 countries and employs more than 194,000 people.
This summer it overtook Samsung as the world’s biggest seller of smartphones… boast some of the most advanced artificial intelligence capabilities on the market.
spending more than 10% of its annual profits on research and development. In 2019 it spent over $15bn — more than Apple and Microsoft — and the budget for 2020 is $20bn. (For comparison, the R&D spend of the entire German car industry in 2018 was roughly $30bn.)
Huawei and 5G are only a small part of a much larger geoeconomic and geopolitical struggle in which China is trying to gain the upper hand over the US.
Washington’s campaign against Chinese tech includes firms such as the state-owned ZTE, another important player in the 5G field, WeChat and TikTok and many other lesser-known companies. But Huawei is its main target.
Washington sees Huawei as an arch-example of China’s rogue behaviour (widely mistaken for meritocratic market success) — stealing intellectual property, bullying partners and undercutting competitors
Behind the Scenes: Microsoft’s Principal Researcher Eyal Ofek speaking about technical and social perspectives of XR
About this Event
The XR Bootcamp Open Lecture Series continues with Microsoft’s Principal Researcher Eyal Ofek!
Agenda:
Virtual Reality (VR) & Augmented reality (AR) pose challenges and opportunities from both a technical and social perspective. We could now have digital, and not physical objects change our understanding of the world around us. It is a unique opportunity to change reality as we sense it.
The Microsoft Researchers are looking for new possibilities to extend our abilities when we are not bound by our physical limitations, enabling superhuman abilities on one hand, and leveling the playfield for people with physical limitations.
Dr. Ofek will describe efforts to design VR & AR applications that will adjust according to the user’s uncontrolled environment, enabling a continuous use during work and leisure, over the large variance of environments. He will also review efforts to the extent the rendering to new capabilities such as haptic rendering.
His lecture will be followed by a Q&A session where you can ask all your questions about the topic.
Lead Instructors:
Eyal Ofek is a principal researcher at the Microsoft Research lab in Redmond, WA. His research interests include Augmented Reality (AR)/Virtual Reality (VR), Haptics, interactive projection mapping, and computer vision for human-computer interaction. He is also the Specialty Chief Editor of Frontiers in Virtual Reality, for the area of Haptics and an Assoc. Editor of IEEE Computer Graphics and Application (CG&A).
Prior to joining Microsoft Research, he obtained his Ph.D. at the Hebrew University of Jerusalem and has founded a couple of companies in computer graphics, including a successful drawing and photo editing application and developing the world’s first time-of-flight video cameras which was a basis for the HoloLens depth camera.
This event is part of the Global XR Bootcamp event:
The Global XR Bootcamp 2020 will be the biggest community-driven, FREE, online Virtual, Augmented and Mixed Reality event in the world! Join us on YouTube or AltspaceVR for a 24 hour live stream with over 50 high quality talks, panels and sessions. Meet your fellow XR enthousiasts in our Community Zone, and win amazing prizes – from vouchers to XR hardware.
Like all of 8th Wall’s WebAR capabilities, projects created using Curved Image Targets work across iOS and Android devices with an estimated reach of nearly 3 billion smartphones, and can be immediately experienced with the tap of a link or by scanning a QR code.
Investment continues to flow to ed tech, with $803 million injected during the first six months of the year, according to the industry news website EdSurge. But half of that went to just six companies, including the celebrity tutorial provider MasterClass, the online learning platform Udemy and the school and college review site Niche.
From the outside, the ed-tech sector may appear as if “there’s a bonanza and it’s like the dot-com boom again and everybody’s printing money,” said Michael Hansen, CEO of the K-12 and higher education digital learning provider Cengage. “That is not the case.”
Even if they want to buy more ed-tech tools, meanwhile, schools and colleges are short on cash. Expenses for measures to deal with Covid-19 are up, while budgets are expected to be down.
Analysts and industry insiders now expect a wave of acquisitions as already-dominant brands like these seek to corner even more of the market by snatching up smaller players that provide services they don’t.
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Tech-based contact tracing could put schools in murky privacy territory
A white paper from the Surveillance Technology Oversight Project (STOP) suggests the use of contact tracing technology by schools could erode student privacy and may not be effective in preventing the spread of coronavirus.
Despite the pandemic, schools still must conform to the Family Educational Rights and Privacy Act (FERPA) and other laws governing student privacy. Districts can disclose information to public health officials, for example, but information can’t be released to the general public without written consent from parents.
The Safely Reopen Schools mobile app is one tool available for automating contact tracing. The idea is that if two mobile phones are close enough to connect via Bluetooth, the phone owners are close enough to transmit the virus. The app includes daily health check-ins and educational notifications, but no personal information is exchanged between the phones, and the app won’t disclose who tested positive.
Colleges are also using apps to help trace and track students’ exposure to coronavirus. In August, 20,000 participants from the University of Alabama at Birmingham were asked to test the GuideSafe mobile app, which will alert them if they’ve been in contact with someone who tested positive for COVID-19. The app determines the proximity of two people through cell phone signal strength. If someone reports they contracted the virus, an alert will be sent to anyone who has been within six feet of them for at least 15 minutes over the previous two weeks.
Critics of the technology claim these apps aren’t actually capable of contract tracing and could undermine manual efforts to do so.
how to increase engagement without relying on “cameras on” and asks instructors to be open to different “shapes” of what engagement can look like: “Many teachers have a shape that they think attention and engagement look like, and they work very hard to get students into that shape.” She also has written about forcing students to turn on their cameras from a trauma-informed perspective.
The researchers reexamined 56 peer-reviewed, published papers that conducted 90 fMRI experiments, some by leaders in the field, and also looked at the results of so-called “test/retest” fMRIs, where 65 subjects were asked to do the same tasks months apart. They found that of seven measures of brain function, none had consistent readings.
Bibliographical data analysis with Zotero and nVivo
Bibliographic Analysis for Graduate Students, EDAD 518, Fri/Sat, May 15/16, 2020
This session will not be about qualitative research (QR) only, but rather about a modern 21st century approach toward the analysis of your literature review in Chapter 2.
However, the computational approach toward qualitative research is not much different than computational approach for your quantitative research; you need to be versed in each of them, thus familiarity with nVivo for qualitative research and with SPSS for quantitative research should be pursued by any doctoral student.
Once you complete the overview of the resources above, please make sure you have Zotero working on your computer; we will be reviewing the Zotero features before we move to nVivo.
Familiarity with Zotero is a prerequisite for successful work with nVivo, so please if you are already working with Zotero, try to expand your knowledge using the materials above.
Please use this link to install nVivo on your computer. Even if we were not in a quarantine and you would have been able to use the licensed nVivo software on campus, for convenience (working on your dissertation from home), most probably, you would have used the shareware. Shareware is fully functional on your computer for 14 days, so calculate the time you will be using it and mind the date of installation and your consequent work.
For the purpose of this workshop, please install nVivo on your computer early morning on Saturday, May 16, so we can work together on nVivo during the day and you can continue using the software for the next two weeks.
Please familiarize yourself with the two articles assigned in the EDAD 815 D2L course content “Practice Research Articles“ :
Brosky, D. (2011). Micropolitics in the School: Teacher Leaders’ Use of Political Skill and Influence Tactics. International Journal of Educational Leadership Preparation, 6(1). https://eric.ed.gov/?id=EJ972880
Tooms, A. K., Kretovics, M. A., & Smialek, C. A. (2007). Principals’ perceptions of politics. International Journal of Leadership in Education, 10(1), 89–100. https://doi.org/10.1080/13603120600950901
It is very important to be familiar with the articles when we start working with nVivo.
whereas the snapshots are replaced with snapshots from nVivol, version 12, which we will be using in our course and for our dissertations.
Concept of bibliographic data
Bibliographic Data is an organized collection of references to publish in literature that includes journals, magazine articles, newspaper articles, conference proceedings, reports, government and legal publications. The bibliographical data is important for writing the literature review of a research. This data is usually saved and organized in databases like Mendeley or Endnote. Nvivo provides the option to import bibliographical data from these databases directly. One can import End Note library or Mendeley library into Nvivo. Similar to interview transcripts, one can represent and analyze bibliographical data using Nvivo. To start with bibliographical data representation, this article previews the processing of literature review in Nvivo.
Importing bibliographical data
Bibliographic Data is imported using Mendeley, Endnote and other such databases or applications that are supported with Nvivo. Bibliographical data here refers to material in the form of articles, journals or conference proceedings. Common factors among all of these data are the author’s name and year of publication. Therefore, Nvivo helps to import and arrange these data with their titles as author’s name and year of publication. The process of importing bibliographical data is presented in the figures below.
select the appropriate data from external folder
Coding strategies for literature review
Coding is a process of identifying important parts or patterns in the sources and organizing them in theme node. Sources in case of literature review include material in the form of PDF. That means literature review in Nvivo requires grouping of information from PDF files in the forms of theme nodes. Nodes directly do not create content for literature review, they present ideas simply to help in framing a literature review. Nodes can be created on the basis of theme of the study, results of the study, major findings of the study or any other important information of the study. After creating nodes, code the information of each of the articles into its respective codes.
Nvivo allows coding the articles for preparing a literature review. Articles have tremendous amount of text and information in the forms of graphs, more importantly, articles are in the format of PDF. Since Nvivo does not allow editing PDF files, apply manual coding in case of literature review. There are two strategies of coding articles in Nvivo.
Code the text of PDF files into a new Node.
Code the text of PDF file into an existing Node. The procedure of manual coding in literature review is similar to interview transcripts.
The Case Nodes of articles are created as per the author name or year of the publication.
For example: Create a case node with the name of that author and attach all articles in case of multiple articles of same Author in a row with different information. For instance in figure below, five articles of same author’s name, i.e., Mr. Toppings have been selected together to group in a case Node. Prepare case nodes like this then effortlessly search information based on different author’s opinion for writing empirical review in the literature.
Nvivo questions for literature review
Apart from the coding on themes, evidences, authors or opinions in different articles, run different queries based on the aim of the study. Nvivo contains different types of search tools that helps to find information in and across different articles. With the purpose of literature review, this article presents a brief overview of word frequency search, text search, and coding query in Nvivo.
Word frequency
Word frequency in Nvivo allows searching for different words in the articles. In case of literature review, use word frequency to search for a word. This will help to find what different author has stated about the word in the article. Run word frequency on all types of sources and limit the number of words which are not useful to write the literature.
For example, run the command of word frequency with the limit of 100 most frequent words . This will help in assessing if any of these words remotely provide any new information for the literature (figure below).
and
and
Text search
Text search is more elaborative tool then word frequency search in Nvivo. It allows Nvivo to search for a particular phrase or expression in the articles. Also, Nvivo gives the opportunity to make a node out of text search if a particular word, phrase or expression is found useful for literature.
For example: conduct a text search query to find a word “Scaffolding” in the articles. In this case Nvivo will provide all the words, phrases and expression slightly related to this word across all the articles (Figure 8 & 9). The difference between test search and word frequency lies in generating texts, sentences and phrases in the latter related to the queried word.
Coding query
Apart from text search and word frequency search Nvivo also provides the option of coding query. Coding query helps in literature review to know the intersection between two Nodes. As mentioned previously, nodes contains the information from the articles. Furthermore it is also possible that two nodes contain similar set of information. Therefore, coding query helps to condense this information in the form of two way table which represents the intersection between selected nodes.
For example, in below figure, researcher have search the intersection between three nodes namely, academics, psychological and social on the basis of three attributes namely qantitative, qualitative and mixed research. This coding theory is performed to know which of the selected themes nodes have all types of attributes. Like, Coding Matrix in figure below shows that academic have all three types of attributes that is research (quantitative, qualitative and mixed). Where psychological has only two types of attributes research (quantitative and mixed).
In this way, Coding query helps researchers to generate intersection between two or more theme nodes. This also simplifies the pattern of qualitative data to write literature.
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Please do not hesitate to contact me with questions, suggestions before, during or after our workshop and about ANY questions and suggestions you may have about your Chapter 2 and, particularly about your literature review:
