59 Matching Annotations
  1. Feb 2024
    1. Assigning credits to learning outcomes allows for the accumulationof units of learning and provides for transferability from one setting to another forvalidation and recognition. Interviewees representing countries in which VETsystems are modularised indicated that modules are designed to indicate a set oflearning outcomes that are expressed in terms of credits. The interviewees fromnational authorities and VET providers commonly agreed that the introduction ofmodular structures in VET and the application of a learning outcomes-basedapproach was set to provide more individualised training paths, enabling accessand progression for learners.

      Align Learning Outcomes to Credits (key for meaningful unbundling/bundling)

    2. The European approach to microcredentials(European Commission, 2020a) also highlights the importance of clearly definedlearning outcomes as a way to promote overall transparency and provide detailedinformation regarding what a learner is expected to know and is able to do

      Purpose of Learning Outcomes

  2. Jan 2024
    1. Searching as exploration. White and Roth [71 ,p.38] define exploratory search as a “sense making activity focusedon the gathering and use of information to foster intellectual de-velopment.” Users who conduct exploratory searches are generallyunfamiliar with the domain of their goals, and unsure about howto achieve them [ 71]. Many scholars have investigated the mainfactors relating to this type of dynamic task, such as uncertainty,creativity, innovation, knowledge discovery, serendipity, conver-gence of ideas, learning, and investigation [2, 46, 71].These factors are not always expressed or evident in queriesor questions posed by a searcher to a search system.

      Sometimes, search is not rooted in discovery of a correct answer to a question. It's about exploration. Serendipity through search. Think Michael Lewis, Malcolm Gladwell, and Latif Nasser from Radiolab. The randomizer on wikipedia. A risk factor of where things trend with advanced AI in search is an abandonment of meaning making through exploration in favor of a knowledge-level pursuit that lacks comparable depth to more exploratory experiences.

  3. May 2023
  4. Apr 2023
    1. One way to weed those out is to begin with the most basic question we can formulate. Conceptual artist Jonathon Keats calls these “naive questions.” Geochemist Hope Jahren calls them “curiosity questions.” Whatever the label, they are, in essence, the kind of question a child could come up with.Progressing from such questions requires us to dig deeper and slow down our thinking — which, in turn, may reveal to us unknown unknowns or information we may have missed last time we explored the topic.

      For the intellectual worker, an Antinet can be used to keep track of such questions and the thought-lines corresponding to these questions.

  5. Mar 2023
    1. As a teacher of English to secondary school students, and as an online doctoral student, I am excited to explore and possibly integrate Hypothesis into my work. I love research and everything involved with it. Thank you to the creators of this tool --

    1. Divergence and emergence allow networked thinkers to uncover non-obvious interconnections and explore second-order consequences of seemingly isolated phenomena. Because it relies on undirected exploration, networked thinking allows us to go beyond common sense solutions.

      The power of an Antinet Zettelkasten. Use this principle both in research and learning.

  6. Feb 2023
    1. “Writing a thesis,”Eco wrote, “requires a student to organize ideas and data, towork methodically, and to build an ‘object’ that in principlewill serve others. In reality, the research experience mattersmore than the topic.”

      Where does the learning portion of education morph into research? Where is the dividing line?

  7. Nov 2022
    1. Quadrants I and II: The average student’s scores on basic skills assessments increase by21 percentiles when engaged in non-interactive, multimodal learning (includes using textwith visuals, text with audio, watching and listening to animations or lectures that effectivelyuse visuals, etc.) in comparison to traditional, single-mode learning. When that situationshifts from non-interactive to interactive, multimedia learning (such as engagement insimulations, modeling, and real-world experiences – most often in collaborative teams orgroups), results are not quite as high, with average gains at 9 percentiles. While notstatistically significant, these results are still positive.

      I think this is was Thomas Frank was referring to in his YT video when he said "direct hands-on experience ... is often not the best way to learn something. And more recent cognitive research has confirmed this and shown that for basic concepts a more abstract learning model is actually better."

      By "more abstract", I guess he meant what this paper calls "non-interactive". However, even though Frank claims this (which is suggested by the percentile increases shown in Quadrants I & II), no variance is given and the authors even state that, in the case of Q II (looking at percentile increase of interactive multimodal learning compared to interactive unimodal learning), the authors state that "results are not quite as high [as the non-interactive comparison], with average gains at 9 percentiles. While not statistically significant, these results are still positive." (emphasis mine)

      Common level of signifcances are \(\alpha =.20,~.10,~.05,~.01\)

  8. Oct 2022
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  10. Aug 2022
  11. Jun 2022
    1. One of my frustrations with the “science of learning” is that to design experiments which have reasonable limits on the variables and can be quantitatively measured results in scenarios that seem divorced from the actual experience of learning.

      Is the sample size of learning experiments really large enough to account for the differences in potential neurodiversity?

      How well do these do for simple lectures which don't add mnemonic design of some sort? How to peel back the subtle differences in presentation, dynamism, design of material, in contrast to neurodiversities?

      What are the list of known differences? How well have they been studied across presenters and modalities?

      What about methods which require active modality shifts versus the simple watch and regurgitate model mentioned in watching videos. Do people do actively better if they're forced to take notes that cause modality shifts and sensemaking?

  12. May 2022
  13. Apr 2022
  14. Feb 2022
    1. Who can blame you forprocrastinating if you find yourself stuck with a topic you decided onblindly and now have to stick with it as the deadline is approaching?

      Students may potentially built up enough context within a particular course to be able to luckily stumble upon an interesting question or idea about which to write, but the procrastination and wait times required to get lucky means that they don't have enough time to research and read additional material to move towards ultimate solutions. As a result, their work product is boring and dull and doesn't advance the space in which they're working. And these are the lucky ones which will stumble upon something interesting or be able to remember it. The results of the rest will be even less interesting.

  15. Nov 2021
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  20. Jan 2021
    1. The best people in empirical fields are typically those who have accumulated the biggest set of experiences and there’s essentially two ways to do this.Spend lots of time doing itGet really good at running many concurrent experiments

      How to derive with the best research

  21. Oct 2020
    1. It is essential to help students develop research abilities in the classroom and through faceted assignments.  What are faceted assignments?  After providing guidance in class, the professor assigns each aspect of a research assignment – development of a research problem statement, location of relevant resources, evaluation of resources, and so on – as its own mini-assignment, which is graded promptly, with sufficient comments to enable students to revise and resubmit.  By the time the final research assignment is complete, it carries the benefit of a significant amount professorial mentoring.

      Research skills involve complex, higher order tasks, and they take long-term efforts to learn well. Adult students are better able to do research than younger students do. They need to learn how to understand the different sources available, formulate good questions, learn more advanced database searching skills, and hone their critical thinking skills. Instead of assigning a research paper, instructors should assign each step of the paper so that they can help students properly master the whole process. 8/10

    1. METHODOLOGY DEVELOPMENT IN ADULT LEARNING RESEARCHCOMBINING PHYSIOLOGICAL REACTIONS AND LEARNING EXPERIENCES IN SIMULATION-BASED LEARNING ENVIRONMENTS

      This article details the methods and results of a research experiment done to determine whether/ how physiological measurement technologies can be used with educational research methods to investigate subjective learning experiences. Describes research methods and data collected. 8/10, very interesting article and a very interesting and well done study but very specific to this one topic. e

  22. Sep 2020
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  27. Mar 2020
    1. Research in Educational Technology

      This textbook, published by the Oklahoma State University Library ePress, contains a chapter which summarizes the main views of knowledge in educational technology research, including postpositivism, constructivism, advocacy, and pragmatism, as well as each view's research traditions. The chapter suggests an approach to evaluating research articles through the lenses of a consistent learning theory coupled, methodologies that support that learning theory, and the conclusions that are drawn by the researchers supported through their methodologies. This chapter would help educators evaluate how and why they might include technology into their course curriculum. Rating: 7/10

  28. Jan 2020
    1. Summarizing a paper in your own words restructures the content to focus on learning rather than novelty.

      In the scientific papers we convey novelty, hence, some of the early readers might confuse themselves that this is the right way to speak in a daily scientific community

    2. Blogging has taught me how to read a paper because explaining something is a more active form of understanding. Now I summarize the main contribution in my own words, write out the notation and problem setup, define terms, and rederive the main equations or results. This process mimics the act of presenting and is great practice for it.

      Why teaching others/blogging has a great value in terms of learning new topics

    3. When I first started teaching myself to program, I felt that I had no imagination. I couldn’t be creative because I was too focused on finding the syntax bug or reasoning about program structure. However, with proficiency came creativity. Programming became less important than what I was building and why.

      While learning, don't worry about the creativity, which shall come after gaining proficiency (knowledge base)

    4. In my opinion the reason most people fail to do great research is that they are not willing to pay the price in self-development. Say some new field opens up that combines field XXX and field YYY. Researchers from each of these fields flock to the new field. My experience is that virtually none of the researchers in either field will systematically learn the other field in any sort of depth. The few who do put in this effort often achieve spectacular results.

      I think we all know that...

  29. Nov 2019
  30. Mar 2019
    1. What's possible with personalized learning: an overview of personalized learning for schools, families, and communities. This 32 page PDF is included in part due to its credibility and also to its breadth. The focus is personalized learning in schools. All ages are considered and there is a discussion of 'what personalized learning means for teachers.' It is sufficiently readable and rather attractively presented for a report. rating 5/5

    1. A national landscape scan of personalized learning in K-12 education in the United States This is included because it is associated with the Bill and Melinda Gates foundation, among other indicators of credibility, and because it provides (as the title suggests) a portrait of the state of personalized learning in schools, addressing topics that are not addressed by other resources in this list. rating 5/5

    1. This online journal article is a reflective piece about mobile learning for teachers. It appears to be connected to the work of Argyris and Schon (reflection in action) and it appears that they argue that adoption of mobile learning for teachers is not occurring at a fast pace. While disappointing, the article appears useful. rating 5/5

    1. This is a research based report (of which I have found few) that connects professional development and personalized learning. I had hoped to find links that applied to health care and have not found a great many so far, but this article, which is more oriented toward professional development for teachers, still has applications since public health education professionals participate in many of the same practices. rating; 5/5

  31. Nov 2018
    1. Instructional Design Strategies for Intensive Online Courses: An Objectivist-Constructivist Blended Approach

      This was an excellent article Chen (2007) in defining and laying out how a blended learning approach of objectivist and constructivist instructional strategies work well in online instruction and the use of an actual online course as a study example.

      RATING: 4/5 (rating based upon a score system 1 to 5, 1= lowest 5=highest in terms of content, veracity, easiness of use etc.)

  32. Apr 2018
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  35. Dec 2017
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  37. Apr 2017
    1. Really cool venue for publishing online, interactive articles for ML

  38. Mar 2017
  39. Feb 2017
  40. Sep 2016
    1. Research: Student data are used to conduct empirical studies designed primarily to advance knowledge in the field, though with the potential to influence institutional practices and interventions. Application: Student data are used to inform changes in institutional practices, programs, or policies, in order to improve student learning and support. Representation: Student data are used to report on the educational experiences and achievements of students to internal and external audiences, in ways that are more extensive and nuanced than the traditional transcript.

      Ha! The Chronicle’s summary framed these categories somewhat differently. Interesting. To me, the “application” part is really about student retention. But maybe that’s a bit of a cynical reading, based on an over-emphasis in the Learning Analytics sphere towards teleological, linear, and insular models of learning. Then, the “representation” part sounds closer to UDL than to learner-driven microcredentials. Both approaches are really interesting and chances are that the report brings them together. Finally, the Chronicle made it sound as though the research implied here were less directed. The mention that it has “the potential to influence institutional practices and interventions” may be strategic, as applied research meant to influence “decision-makers” is more likely to sway them than the type of exploratory research we so badly need.

    1. the use of data in scholarly research about student learning; the use of data in systems like the admissions process or predictive-analytics programs that colleges use to spot students who should be referred to an academic counselor; and the ways colleges should treat nontraditional transcript data, alternative credentials, and other forms of documentation about students’ activities, such as badges, that recognize them for nonacademic skills.

      Useful breakdown. Research, predictive models, and recognition are quite distinct from one another and the approaches to data that they imply are quite different. In a way, the “personalized learning” model at the core of the second topic is close to the Big Data attitude (collect all the things and sense will come through eventually) with corresponding ethical problems. Through projects vary greatly, research has a much more solid base in both ethics and epistemology than the kind of Big Data approach used by technocentric outlets. The part about recognition, though, opens the most interesting door. Microcredentials and badges are a part of a broader picture. The data shared in those cases need not be so comprehensive and learners have a lot of agency in the matter. In fact, when then-Ashoka Charles Tsai interviewed Mozilla executive director Mark Surman about badges, the message was quite clear: badges are a way to rethink education as a learner-driven “create your own path” adventure. The contrast between the three models reveals a lot. From the abstract world of research, to the top-down models of Minority Report-style predictive educating, all the way to a form of heutagogy. Lots to chew on.

  41. Dec 2015