Author Archives: lucaslongo

Engineering Education – Week 3 – Group Meeting

Met with James and Camila about this class’ final project – which will be my Master’s project. Discussed what were the interventions I imagined we could do with the instructors and we all seemed to agree with what could be done.

IMG_2627.JPG

While we were in the meeting, we were ‘visited’ by a photographer who wanted to take some pictures of the classroom we were in.

Later on I received an email from her 🙂

Hello,

 Yesterday I wandered into a classroom and took a couple of pictures of you talking about course design.  I work at Stanford in the VPGE office, and I also (on the side) write a blog about graduate education. I am working on a post related to a newly released study about the value of teaching development activities for grad students (lsfss.wceruw.org). My blog is here:  http://gradlogic.org 

I wanted to know whether it was ok to use one of these photos. Your face isn’t shown.  I may also want to use them later, but only if it is ok with you.

Thanks,

Chris M. Golde
chris@golde.org
GRAD | LOGIC blog
Helping graduate students navigate the ups and downs of graduate school
http://gradlogic.org 

 Arm with boardArm with board 2

Engineering Education – Week 3.1 – Class Notes

Reading:

Ambrose, S. A., Bridges, M. W., DiPietro, M., Lovett, M. C., & Norman, M. K. (2010). How learning works: Seven research-based principles for smart teaching. John Wiley & Sons.

Summary: 

The first chapter illustrates how Prior Knowledge can affect learning both positively and negatively. When dealing with counterituitive concepts especially, common misconceptions that root from inacurate Prior Knowledge, are very hard to change and require time, cognitive energy, and an attentive teacher to scaffold the process. I appreciated all the methods offered to gauge, activate, recognize, and suplement Prior Knowledge as well as correct inacurate Prior Knowlege.

The second chapter goes into how students organize knowledge and how might a teacher build these schemas more effectively on them. It is important for the teacher to realize that students come into a new subject area with  shallow understanding of how apparently  unconnected peices of knowledge relate to each other. This richness of connections is one of the abilities that makes someone an expert. Therefore, the more the teacher is able to demonstrate how to build these connections and organize the information in an effective manner, the more students might learn.

“…it is not just what you know but how you organize what you know that influences learning and performance. ” (Ambrose et al., 2010)

Notes:

Chapter 1 – How Does Student’s Prior Knowledge Affect Their Learning?

  • Principle: Students’ prior knowledge can help or hinder learning.
    • Help to make connections
    • Hinder with misconceptions that carry forward
      • “If they do not draw on relevant prior knowledge—in other words, if that knowledge is inactive—it may not facilitate the integration of new knowledge. Moreover, if students’ prior knowledge is insufficient for a task or learning situation, it may fail to support new knowledge, whereas if it is inappropriate for the context or inaccurate, it may actively distort or impede new learning” (Ambrose et al., 2010)07F9A469-4C93-435E-91B9-FE1D1B6CB869
  • Activating Prior Knowledge
    • Teacher must probe and activate knowledge from the student – simply mentioning it sometimes already does the trick
      • “In other words, with minor prompts and simple reminders, instructors can activate relevant prior knowledge so that students draw on it more effectively (Bransford & Johnson, 1972; Dooling & Lachman, 1971).” (Ambrose et al., 2010)
  • Accurate but Insufficient Knowledge
    • Declarative Knowledge
      • Recite facts
    • Procedural Knowledge
      • How to do it
    • You can have one and not the other, and vice-versa
  • Inappropriate Prior Knowledge
    • Knowledge that hinders understanding of “counterintuitive” concepts
    • Teachers must attend to:
      • Explain conditions and contexts of applicability
      • Abstract principles with multiple examples and contexts
      • Analogies – differences and similarities
      • Activate prior knowledge to strengthen appropriate associations
  • Inacurate Prior Knowledge
    • Misconceptions
      • Extremely hard to correct
      • Require greater cognitive energy
      • Conceptual changes occur over time
    • Bridging
      • Concepts that act as intermediaries between misconception and desired concepts
  • Methods
    • Gauge the Extent and Nature of Students’ Prior Knowledge
      • Talk to colleagues
      • Diagnostic assessments
        • Short, low-stakes assessments
        • Quiz or essay
        • At the beginning
        • Concept inventories
          • Reveal common misconceptions
      • Students assess own Prior Knowledge
        • Cursory familiarity: “I have heard of the term”
        • Factual knowledge: “I could define it”
        • Conceptual knowledge: “I could explain it to someone else”
        • Application: “I can use it to solve problems”
      • Brainstorming to reveal Prior Knowledge
      • Concept map activity
      • Patterns of error in student work
    • Activate accurate Prior Knowledge
      • Exercises to generate students’ Prior Knowledge
        • can generate inaccurate and inappropriate as well as accurate and relevant knowledge
      • Link new material to materials in other courses
      • Link new material to materials in your own course
      • Analogies and examples to link to Everyday Knowledge
      • Reason on the basis of Prior Knowledge
    • Insufficient Prior Knowledge
      • Identify Prior Knowledge you expect students to have
      • Remediate insufficient Prerequisite Knowledge
    • Recognize Inappropriate Prior Knowledge
      • Conditions of applicability
      • Heuristics to avoid inappropriate application of knowledge
      • Identify discipline-specific conventions
      • Show where analogies break down
    • Correct Inacurate Knowledge
      • Students to make and test predictions
      • Justify their reasoning
      • Opportunities to use accurate knowledge
      • Allow sufficient time

Chapter 2: How Does the Way Students Organize Knowledge Affect Their Learning?

  • Principle: How students organize knowledge influences how they learn and apply what they know.
    • Teach students how to organize content as experts do

Screen Shot 2016-04-11 at 8.27.41 AM.png

  • Form fits function
    • The way you organize knowledge affects how you apply knowledge
    • “we need to provide students with appropriate organizing schemes or teach them how to abstract the relevant principles from what they are learning.” (Ambrose et al., 2010)
  • Strategies:
    • Reveal and enhance knowledge organization
      • Concept maps of your own
      • Associate tasks with organizations
      • Show organization of course, lectures, lab, or discussions
      • Contrasting and boundary cases to highlight organization features
      • Deep features – make them explicit
      • Explicitly make connections
      • Work with multiple organization structures
      • Concept maps that show student’s knowledge organizations
      • Sorting tasks that show student’s knowledge organizations
      • Monitor student’s work
  • Conclusion:
    • “…it is not just what you know but how you organize what you know that influences learning and performance. ” (Ambrose et al., 2010)

    • Engineering Education – Week 3.1 – Reading Summary

    Reading:

    Ambrose, S. A., Bridges, M. W., DiPietro, M., Lovett, M. C., & Norman, M. K. (2010). How learning works: Seven research-based principles for smart teaching. John Wiley & Sons.

    Summary: 

    The first chapter illustrates how Prior Knowledge can affect learning both positively and negatively. When dealing with counterituitive concepts especially, common misconceptions that root from inacurate Prior Knowledge, are very hard to change and require time, cognitive energy, and an attentive teacher to scaffold the process. I appreciated all the methods offered to gauge, activate, recognize, and suplement Prior Knowledge as well as correct inacurate Prior Knowlege.

    The second chapter goes into how students organize knowledge and how might a teacher build these schemas more effectively on them. It is important for the teacher to realize that students come into a new subject area with  shallow understanding of how apparently  unconnected peices of knowledge relate to each other. This richness of connections is one of the abilities that makes someone an expert. Therefore, the more the teacher is able to demonstrate how to build these connections and organize the information in an effective manner, the more students might learn.

    “…it is not just what you know but how you organize what you know that influences learning and performance. ” (Ambrose et al., 2010)

    Notes:

    Chapter 1 – How Does Student’s Prior Knowledge Affect Their Learning?

    • Principle: Students’ prior knowledge can help or hinder learning.
      • Help to make connections
      • Hinder with misconceptions that carry forward
        • “If they do not draw on relevant prior knowledge—in other words, if that knowledge is inactive—it may not facilitate the integration of new knowledge. Moreover, if students’ prior knowledge is insufficient for a task or learning situation, it may fail to support new knowledge, whereas if it is inappropriate for the context or inaccurate, it may actively distort or impede new learning” (Ambrose et al., 2010)07F9A469-4C93-435E-91B9-FE1D1B6CB869
    • Activating Prior Knowledge
      • Teacher must probe and activate knowledge from the student – simply mentioning it sometimes already does the trick
        • “In other words, with minor prompts and simple reminders, instructors can activate relevant prior knowledge so that students draw on it more effectively (Bransford & Johnson, 1972; Dooling & Lachman, 1971).” (Ambrose et al., 2010)
    • Accurate but Insufficient Knowledge
      • Declarative Knowledge
        • Recite facts
      • Procedural Knowledge
        • How to do it
      • You can have one and not the other, and vice-versa
    • Inappropriate Prior Knowledge
      • Knowledge that hinders understanding of “counterintuitive” concepts
      • Teachers must attend to:
        • Explain conditions and contexts of applicability
        • Abstract principles with multiple examples and contexts
        • Analogies – differences and similarities
        • Activate prior knowledge to strengthen appropriate associations
    • Inacurate Prior Knowledge
      • Misconceptions
        • Extremely hard to correct
        • Require greater cognitive energy
        • Conceptual changes occur over time
      • Bridging
        • Concepts that act as intermediaries between misconception and desired concepts
    • Methods
      • Gauge the Extent and Nature of Students’ Prior Knowledge
        • Talk to colleagues
        • Diagnostic assessments
          • Short, low-stakes assessments
          • Quiz or essay
          • At the beginning
          • Concept inventories
            • Reveal common misconceptions
        • Students assess own Prior Knowledge
          • Cursory familiarity: “I have heard of the term”
          • Factual knowledge: “I could define it”
          • Conceptual knowledge: “I could explain it to someone else”
          • Application: “I can use it to solve problems”
        • Brainstorming to reveal Prior Knowledge
        • Concept map activity
        • Patterns of error in student work
      • Activate accurate Prior Knowledge
        • Exercises to generate students’ Prior Knowledge
          • can generate inaccurate and inappropriate as well as accurate and relevant knowledge
        • Link new material to materials in other courses
        • Link new material to materials in your own course
        • Analogies and examples to link to Everyday Knowledge
        • Reason on the basis of Prior Knowledge
      • Insufficient Prior Knowledge
        • Identify Prior Knowledge you expect students to have
        • Remediate insufficient Prerequisite Knowledge
      • Recognize Inappropriate Prior Knowledge
        • Conditions of applicability
        • Heuristics to avoid inappropriate application of knowledge
        • Identify discipline-specific conventions
        • Show where analogies break down
      • Correct Inacurate Knowledge
        • Students to make and test predictions
        • Justify their reasoning
        • Opportunities to use accurate knowledge
        • Allow sufficient time

    Chapter 2: How Does the Way Students Organize Knowledge Affect Their Learning?

    • Principle: How students organize knowledge influences how they learn and apply what they know.
      • Teach students how to organize content as experts do

    Screen Shot 2016-04-11 at 8.27.41 AM.png

      • Form fits function
        • The way you organize knowledge affects how you apply knowledge
        • “we need to provide students with appropriate organizing schemes or teach them how to abstract the relevant principles from what they are learning.” (Ambrose et al., 2010)
      • Strategies:
        • Reveal and enhance knowledge organization
          • Concept maps of your own
          • Associate tasks with organizations
          • Show organization of course, lectures, lab, or discussions
          • Contrasting and boundary cases to highlight organization features
          • Deep features – make them explicit
          • Explicitly make connections
          • Work with multiple organization structures
          • Concept maps that show student’s knowledge organizations
          • Sorting tasks that show student’s knowledge organizations
          • Monitor student’s work
    • Conclusion:
      • “…it is not just what you know but how you organize what you know that influences learning and performance. ” (Ambrose et al., 2010)

    Engineering Education – Week 2.1 – Reading Notes

    Means, B., Bakia, M., & Murphy, R. (2014).Learning online: What research tells us about whether, when and how. Routledge.

    Summary:

    Means et al (2014) provide a comprehensive overview of the online learning space with helpful categorizations of the main variables and its attributes. One of the most interesting points, besides the finding that online instruction can be as, and sometimes more effective than face-to-face, was that the discussion must move from an overall debate of online or not, this platform or that, to a focus onto how each instructional design principle is effective, for each content type. As in classroom practice, each content area or skills set, requires different pedagogical moves and student interactions with the teacher, the content, and each other. In an online environment, the research and practice must attend to this granularity instead of approaching the use of technology in a generic manner or a technocentric approach. The challenge is that these technological affordances must be used purposefully by the instructors who, for the most part, have had little exposure to online learning environments, might never have been a student in one, and probably has never taken a course on how to create a course online. “People engaged in these activities are often disinclined lo spend time searching the learning sciences literature or selling out to experiment with alternative instructional design principles.” (Means, Bakia, & Murphy, 2014, p37)

    Finally, in the conclusion, Means et al (2014) allude that MOOCs might move a direction of being used more and more across institutions. Does this mean that courses are going to, or should become more centralized? Should Stanford for example have the ‘standard’ Programming 101 course other institutions should use since it’s ‘the best’? The thought of centralizing knowledge is to say the least controversial, yet probably impossible. MOOCs themselves, along with the myriad of LMSes and course marketplaces, allow for anyone to publish their own knowledge – evidently with varying levels of quality and effectiveness. With this in mind I find it particularly interesting to research further into how to provide knowledge sharing tools that scaffold the instructor towards a better and more effective course.

    Notes:

    • Online is as effective as face-to-face
      • “Overall, the preponderance of the meta-analyses suggests that purely online and purely face-to-face instruction usually produce statistically equivalent learning outcomes.” (Means, Bakia, & Murphy, 2014, p22)
    • Technology to enhance, not only substitute
      • “The greatest promise of learning technology lies not in doing what we have always done better, faster, or more cheaply but rather in providing kinds of learning experiences that would be impossible without technology (Fishman & Dede, in preparation).” (Means, Bakia, & Murphy, 2014, p24)
      • “‘Trying to make online education “the same” most likely will lead to less than optimal learning, when, in fact, online education has the potential to support significant paradigm changes in teaching and learning’ (p. 3).” (Means, Bakia, & Murphy, 2014, p24)
    • Differential Attrition Rates
      • Retention rates – research shows winners on both sides
        • For “full courses”, online is worse
    • Online Learning Design Dimensions
      • Modality
        • Fully online
        • Blended with over 50% online but at least 25% FTF
        • Blended with 25-50% online
        • Web-enabled FTF
      • Pacing
        • Self-paced (open entry and open exit)
        • Class-paced
        • Class-paced with some self-paced elements
      • Student-instructor ratio
        • ≤ 35 to 1
        • 36-99 to 1
        • 100-999 to 1
        • ≥ 1000 to 1
      • Pedagogy
        • Expository
        • Practice environment
        • Exploratory
        • Collaborative
      • Instructor role online
        • Active instruction online
        • Small presence online
        • None
      • Student role online
        • Listen or read
        • Complete problems or answer questions
        • Explore simulation and resources
        • Collaborate with peers
      • Online communication synchrony
        • Asynchronous and synchronous
        • Asynchronous only
        • Synchronous only
        • None
      • Roles of online assessments
        • Determine if student ready for new content
        • Tell system how to support the student (basis for adaptive instruction)
        • Provide student or teacher with information about learning state
        • Input to grade
        • identify students at risk of failure
      • Source of feedback
        • Automated
        • Teacher
        • Peers
    • Forms of interaction to be measured/compared
      • Teacher-student
      • Student-student
      • Student-content
    • Learning system options
      • Pacing and time to learn (self-paced learning)
      • Learning objectives (let learners choose their course of study)
      • Content choices for specified learning objectives (e.g., opportunities to choose content to match learner background or interests while working on the same skills or concepts)
      • Content complexity or difficulty level
      • Pedagogy (e.g., a tutorial vs. learn by doing)
      • Degree of learner control (e.g., fixed path through the content for some students while other get to choose their own learning sequence)
      • Types of scaffolding (e.g., hints suggesting what a learner might review verses providing the prerequisite piece of knowledge)
      • Nature and timing of feedback (e.g., information on whether the response was right or wrong versus information on what the learner might do to solve future such problems correctly)
    • Multimedia instructional material guidelines
      • Coherence – reduce extraneous material
      • Signaling – highlight essential material
      • Redundancy – avoid adding on-screen text to narrated animations
      • Spatial contiguity – place printed words next to corresponding graphics
      • Temporal contiguity – present corresponding narration and animation at the same time
    • Design Principles Database
    • Researchers at the Pittsburgh Science of Learning Center (PSLC)
      • Apply research-based design principles on specific knowledge components, not only on entire course
      • Look at how each instructional design principle is effective for each content type
    • Creating online LXs
      • Commercial products do not want to expose their data
      • Labor-intensive to produce
      • Time constraints to launch
      • Not research-based
        • “People engaged in these activities are often disinclined to spend time searching the learning sciences literature or selling out to experiment with alternative instructional design principles.” (Means, Bakia, & Murphy, 2014, p37)
    • Further research – Learning Sciences
      • “The circumstances most conducive to meaningful research on how best to design and implement online learning appear to involve longer-term projects that explicitly bring together learning researchers, instructors, and technology developers with the expectation that the online instruction they produce will be used in multiple settings by multiple instructors and refined over time on the basis of learner data.” (Means, Bakia, & Murphy, 2014, p37)
    • Summary and Conclusions
      • Online instruction can be as effective or sometimes better than face-to-face
        • Blended shows even better results specifically
      • Technology offers distinct benefits
        • Concrete visual representations of abstract concepts
        • Fostering interactivity
        • Immersion learners in complex, lifelike environments and challenges
        • Customizing he pace
        • Constant complexity
        • Interface
        • Amount of scaffolding or individual learners
        • Maintaining automated records of each learner’s actions on the learning system over time
      • Trend towards one course be used ever more widely across institutions
        • Focus on making these courses the best possible
          • “Oracle effect”? One source of information?
      • Need to look at data produced more closely
        • Compare with external assessments

    Lytics Seminar – Week 2 – Class Notes

    2b59e32.jpg

    Good class. Went over research terminology and talked in pairs about each term to clarify any missconceptions. My pair was Anita Tseng, who is doing some very intersting research on common scientific misconception on the internet and social media.

    Quick exercise we did in class… write down our own research goal and discuss with our partners based upon it.

    My Research Goal

    • To understand what are the best practices an instructor should use to create online courses.

    (to do… go through Candace’s slides to evaluate my research question)

    Brazilian Education – Week 2 – Class Notes

    servletrecuperafoto.jpeg

    During class we had the pleasure of hearing Prof. Ulisses Araújo, Director of USP’s Research Center for New Pedagogical Architectures, talk about his work around the “Challenge of Quality Education in Brazil: Technologies and Active Learning Methods as an Answer”. I was honored with the task of being his discussant during the Q&A session.

    Prof. Ulisses also suggested to share the following articles that were closely related to the talk:

    • O uso de tecnologias educacionais na formação de professores para conteúdos de ética e cidadania: o curso de Especialização semipresencial em Ética, valores e cidadania na escola.
      International Studies on Law and Education, v. 19, p. 37-46, 2015.
      ARAUJO, U. F. ; GARBIN, M. C. ; FRANZI, J. ; ARANTES, V. A. ; SILVA, C. O.
      Ler artigo

    • The reorganization of time, space and relationships in school with the use of active learning methodologies and collaborative tools.
      ETD. Educação Temática Digital, v. 16, p. 84-99, 2014.
      ARAUJO, U. F.; FRUCHTER, R.; GARBIN, M. C. ; PASCOALINO, L. N. ; ARANTES, V. A.
      Ler artigo

    Presentation Notes:
    (bold = questions I asked)

    • First true pure online university in Brazil
      • What are the affordances, advantages of being purely online?
        • What are the disadvantages?
    • Education has been historically a ONE-TO-ONE relationship
      • 19th century – classroom is ‘invented’ for the masses
        • Defines the architecture of education
        • Homogeneous
      • 3d revolution of education
        • Universalization
        • Inclusion of all differences in the classroom
    • Need homogeneous classrooms
      • How do you do that without creating an even wider gap in equity?
    • Lower the cost of education
      • Books are more expensive to produce than an online course?
    • Bringing new tools into education
      • Is there a resistance in the academic world to adopt open platforms or even ‘foreign’ technology?
    • Guiding principles
      • Problem and Project-Based Learning
        • Projects are defined by the cohort – a technique to scale up knowledge
        • Design Thinking – without implementation

    Lytics Seminar – Week 2.1 – Reading Notes

    The Research Methods Knowledge Base: 3rd edition by William M.K. Trochim and James P. Donnelly. Chapter 1

    • 1-1 The Language of Research
      • 1-1a Types of Studies (Cumulative)
        • Descriptive
        • Relational: two variables
        • Causal: most demanding
          • Evidence-based practice
      • 1-1b Time in Research
        • Cross-sectional – single point in time
        • Longitudinal studies – over time
          • Repeated measures
            • Two or a few waves of measurement
          • Time series
            • Over 20 waves of measurement
      • 1-1c Type of Relationships
        • Simple correlational relationship – act in synchrony
        • Causal relationship – one explains another
        • Third-Variable problem – something else which affects both variables
        • Patterns
          • No relationship
          • Positive relationship
          • Negative relationship
      • 1-1d Variables
        • Attributes
        • Dependent / Independent
        • Exhaustive: holds all possible values
        • Mutually exclusive: employed, not employed + 2nd job
      • 1-1e Hypotheses
        • Prediction, in concrete terms
        • Not all research has a hypothesis – exploratory
        • Alternative hypothesis
        • Null hypothesis
        • One-tailed hypothesis
      • 1-1f Types of Data
        • Quantitative & Qualitative
          • “All quantitative data is based upon qualitative judgements; and all qualitative data can be described and manipulated numerically.” (Trochim & Donnely, 2006)
      • 1-1f The Unit of Analysis
        • Individuals, Groups, Artifacts, Geo, Social
      • 1-1h Research Fallacies
        • Ecological fallacy – group stereotyping
        • Exception fallacy – one does not represent the group
    • 1-2 Philosophy of Research
      • 1-2a Structure of research
        • Hourglass shape – broad area of interest to measurement and observation to generalize back to question

    Screen Shot 2016-04-04 at 11.51.03 PM.png

        • Components of a study
          • Research problem
          • Research question
          • Program (cause)
          • Units
          • Outcomes (effects)
          • Design
      • 1-2b Deduction and Induction
        • Deductive
          • More general to more specific
          • Top-down approach
        • Inductive
          • From specific to general
          • Bottom-up approach
      • 1-2c Positivism and Post-Positivism
        • Epistemology – philosophy of knowledge
        • Methodology – how
        • Positivism
          • Empiricism – Knowledge as only what could be observed and measured
          • Deterministic
          • Deductive reasoning
        • Post-Positivism
          • Theoretical reasoning & experience-based evidence
          • Probabilistic
          • Critical realism
            • External reality
            • Never accurate (critical)
          • Subjectivist
            • World is solely a creation of your mind
          • Constructivist
            • Reality is a conceptual construction
          • Evolutionary epistemology or natural selection theory of knowledge
            • Ideal have survival value
            • knowledge evolves through a process of variation, selections, and retention (evolution)
      • 1-2d Validity
        • Best available approximation to the truth of a give proposition, inference, or conclusion
        • “Validity of what?”

    Screen Shot 2016-04-06 at 11.41.26 AM.png

        • Four types
          • Conclusion
            • Is there a relationship between cause and effect?
          • Internal
            • Is the relationship causal?
          • Construct
            • Can we generalize to the constructs?
            • Cause Construct
              • Your theory about the cause in a cause-effect relationship
            • Effect Construct
              • Your theory what the outcome is in a cause-effect relationship
          • External
            • Can we generalize to other persons, places, or times?
        • Threat to Validity
          • Reasons why your conclusion or inference might be wrong
        • Conclusion Validity
          • The degree to which your conclusions about relationships in your data are reasonable
    • 1-3 Ethics in Research
      • 1-3a The Language of Ethics
        • Voluntary participation
          • Make sure there is no coercion to participate
        • Informed consent
          • Information about procedures and risks involved
        • Confidentiality
          • Their personal/individual information or identity will not be released beyond the scope of the study
        • Institutional Review Board (IRB)
          • Panel who reviews research proposals with respect to ethical implications
    • 1-4 Conceptualizating
      • Concept Mapping
        • 2D graphs of a group’s ideas – used to develop conceptual framework for a research project
      • 1-4a Problem formulation
        • Comes from practical problems in the field
        • Request for Proposals (RFP)
        • Feasibility
        • Literature Review
      • 1-4b Concept mapping
        • Pictorial representation of ideas
        • Steps:
          • Preparation
          • Generation
          • Structuring
          • Representation
          • Interpretation
          • Utilization
      • 1-4c Logic models

    Nathan, M., & Alibali, M. (2010). Learning sciences. WIREs Cognitive Science.  DOI: 10.1002/wcs.54

    Engineering Education – Week 2.1 – Reading Notes

    Brazilian Education – Week 4 – Class Notes

    UnknownThis week we had a wonderful talk by Kathryn Moeller, Assistant Professor University of Wisconsin, Madison on “The Logic and Consequences of U.S. Transnational Corporate Funding of Girls’ Education in Brazil”

    She talks about Nike’s program called “The Girl Effect” which attempted to help underprivileged girls, and then suddenly stopped the program… and it seemed like they just wanted to tell these girls  not to get pregnant, so that they could be used in the labor market…

    The initiative is now a standalone program that has no more ties with Nike… here’s the very well polished video they came up with to get some initial attention and funding:

    Engineering Education – Week 2.1 – Class Notes

    Final group is set with Camila and James. Rodrigo dropped the course unfortunately. Had our co-teacher Chris Bennett, expert in game design lead the intro session of the “core loop” as we did in the Fall quarter pop-up session.

    Here are a couple of interesting links about CoreLoops:


    gameatoms_Loop.pngAP6_sceloop.png
    We played a very interesting game called ‘Cat On Yer Head‘ where one person was was the ‘cat’ and another was the ‘mouse’. Each person had to repeatedly say cat or mouse aloud. You can transfer the cat or mouse by tapping on someonelses shoulders. The aim is to catch the mouse. 

    Talked about the MDA+Outcomes Approach:IMG_2597

    Core Loop:IMG_2598

    Grand finalle by Candace:IMG_2599