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.


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.


  • 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

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:

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


Engineering Education – Week 2.1 – Summary


  1. Hunicke, R., LeBlanc, M., & Zubek, R. (2004, July). MDA: A formal approach to game design and game research. In Proceedings of the AAAI Workshop on Challenges in Game AI (Vol. 4, p. 1).
  2. Schell, J. (2014). The Art of Game Design: A book of lenses. CRC Press.


I’ve developed mobile apps in one form or another for the past 16 years – from WAP to iOS. These apps were mostly utilitarian and far removed from games. Considering how creating a great user experience was complex and challenging, I’ve always said that games is the most daunting task a development team can undertake. From a technical standpoint, the numbers of variables, mechanics, and rules are enormous and all interconnected. From a creation standpoint, one must envision a whole set of complex interactions between the user and the interface. From a design standpoint, it has too look great!  On top of that, you must take into account the emotional nature of the user interaction with the game. All this requires skills and knowhow that only comes with years of practice – just like teaching.

The readings were extremely helpful in organizing and categorizing some of the considerations, possibilities, and methodologies required when creating a game. The MDA Framework shows how the interaction path of the game developer and the player is opposite, illustrating one of the complexities and iterative nature the game design process can be.

Screen Shot 2016-04-03 at 5.38.55 PMMethod |  Dynamic | Aesthetic

Schell then expands the arsenal by walking us through the several possible lenses we can look at games, the players, their interactions, and even how to improve them. The level of detail we can go into when looking at games is amazing.

How might we new apply these frameworks, insights, and mechanics to education? Can we gamify teaching? If we look at education as a game, could we create better learning experiences for the teacher, the learner, and society? All I know is that we must keep playing this ‘game’ of education, continuously trying to overcome obstacles, making it better, more efficient, and more effective. Can we ever win? We certainly cannot lose.

Engineering Education – Week 2.1 – Reading Notes

Hunicke, R., LeBlanc, M., & Zubek, R. (2004, July). MDA: A formal approach to game design and game research. In Proceedings of the AAAI Workshop on Challenges in Game AI (Vol. 4, p. 1).

  • Mechanics, Dynamics, and Aesthetics (MDA) Framework
    • Formal approach to understanding games
    • Facilitate the conversation between developers, scholars, and researchers.
    • Bridge the gap between game design and development, game criticism, and technical game research
  • Components:
    • Mechanics describes the particular components of the game, at the level of data representation and algorithms.
    • Dynamics describes the run-time behavior of the mechanics acting on player inputs and each others’ outputs over time.
    • Aesthetics describes the desirable emotional responses evoked in the player, when she interacts with the game system.

Screen Shot 2016-04-03 at 5.34.21 PM.png

  • Games
    • More like artifacts than media
    • Purchased, used, and then cast away – consumable product
    • “From the designer’s perspective, the mechanics give rise to dynamic system behavior, which in turn leads to particular aesthetic experiences. From the player’s perspective, aesthetics set the tone, which is born out in observable dynamics and eventually, operable mechanics.” (Hunicke, LeBlanc, & Zubek, 2004, p.2)

Screen Shot 2016-04-03 at 5.38.55 PM.png

  • Aesthetic Models
    • Sensation: Game as sense-pleasure
    • Fantasy: Game as make-believe
    • Narrative: Game as drama
    • Challenge: Game as obstacle course
    • Fellowship: Game as social framework
    • Discovery: Game as uncharted territory
    • Expression: Game as self-discovery
    • Submission: Game as pastime

Schell, J. (2014). The Art of Game Design: A book of lenses. CRC Press.
(Read Chapter 8 Psychographics section & Chapter 10: Mechanics 1-5)

Chapter 8 – Psycographics

  • Demographics : Psychographics
  • LeBlanc’s Taxonomy of Game Pleasures
    • Sensation: using your senses
    • Fantasy: using your imagination
    • Narrative: sequence of events
    • Challenge: problema to be solved
    • Fellowship: social
    • Discovery: pleasure of new things
    • Expression: expresse your self / customize characters
    • Submission: leave one world, go to another, submit to its rules
  • Bartle’s Taxonomy of Player Types
    • Achievers -> Challenge.
    • Explorers -> Discovery.
    • Socializers -> Fellowship.
    • Killers -> not well mapped… competing, defeating others, imposing themselves on others, helping others
  • Not all inclusive: “destruction” and “nurturing” not well mapped for example

Untitled presentation.jpg

  • Pleasures to be considered
    • Anticipation
    • Delight in another’s misfortune
    • Gift Giving
    • Humor
    • Possibility
    • Pride in Accomplishment
    • Purification
    • Surprise
    • Thrill
    • Triumph over Adversity
    • Wonder
      • and the list goes on…
  • Lens #17: The Lens of Pleasure
    • Questions to ask yourself:
      • What pleasures does your game give to players? Can these be improved?
      • What pleasures are missing from your experience? Why? Can they be added
    • Ultimately, the job of a game is to give pleasure.

Chapter 10

  • Mechanic 1: Space
    • Game spaces
      • Are either discrete or continuous
      • Have some number of dimensions
      • Have bounded areas which may or may not be connected
    • Examples
      • Tic-tac-toe
      • Connected areas
      • Nested spaces (Indoor / Outdoor)
      • Zero dimensions (question/answer games)
    • Lens #21: The Lens of Functional Space
      • Space with no surface elements
      • Questions:
        • Is the space of this game discrete or continuous?
        • How many dimensions does it have?
        • What are the boundaries of the space?
        • Are there sub-spaces? How are they connected?
        • Is there more than one useful way to abstractly model the space of this game?
  • Mechanic 2: Objects, Attributes, and States
    • State machine
    • Secrets
      • A: completely public
      • B: 2 & 3 know, 1 does not
      • C: only 1 knows
      • D: games knows, not players
      • E: randomly generated information (Fates, God, etc.)Untitled.001.png
    • Lens #22: The Lens of Dynamic State
      • What information changes during game and who is aware of it
      • Questions:
        • What are the objects in my game?
        • What are the attributes of the objects?
        • What are the possible states for each attribute? What triggers the state changes for each attribute?
        • What state is known by the game only?
        • What state is known by all players?
        • What state is known by some, or only one player?
        • Would changing who knows what state improve my game in some way?
  • Mechanic 3: Actions
    • Operative actions: move checkers forward
    • Resultant actions: protect another checker
      • Very strategic
      • Not part of the rules per se
      • “Most game designers agree that interesting emergent actions are the hallmark of a good game.” 

    • Planting seeds of emergence
      • Add more verbs: related operative actions, but don’t overwhelm user
      • Verbs that can act on many objects: shot not only enemie, but other things
      • Goals that can be achieved more than one way
      • Many subjects: not only one chekcers, many
      • Side effects that change constraints: checker’s move changes gamespace
    • Lens #23: The Lens of Emergence
      • Questions:
        • How many verbs do my players have?
        • How many objects can each verb act on?
        • How many ways can players achieve their goals?
        • How many subjects do the players control?
        • How do side effects change constraints?
      • Stories vs Games
        • Endless possibilites vs. limited actions
      • Allow for all verbs
        • Massively multiplayer games: Second Life
    • Lens #24: The Lens of Action
      • What players can do, what they can’t, and why.
      • Questions:
        • What are the operational actions in my game?
        • What are the resultant actions?
        • What resultant actions would I like to see? How can I change my game in order to make those possible?
        • Am I happy with the ratio of resultant to operational actions?
        • What actions do players wish they could do in my game that they cannot? Can I somehow enable these, either as operational or resultant actions?
  • Mechanic 4: Rules
    • Most fundamental mechanic
    • Rules:
      • Operational: what can you do in the game
      • Foundational: inform operational rules
      • Behavioral: unwritten rules of good sportsmanship
      • Written: no ones reads them -> in-game tutorials
      • Laws: tournament rules
      • Official: merge written rules with the laws
      • Advisory: tips on game mechanics
      • House: feedback, adaptation of gameplay to contextUntitled.001.png
    • Modes
      • Rules change in different modes
    • The Enforcers
      • Traditional games: players themselves
      • Computer games: the game
    • The Most Important Rule
      • Rule that is at the foundation of all others
      • The Object of the Game: explained simply and clearly
      • Chess
        • “Capture the opponent’s King”
      • Good Goals
        • Concrete
        • Achievable
        • Rewarding (look at Lens of Pleasure)
    • Lens #25: The Lens of Goals
      • Appropriate and well-balanced
      • Questions:
        • What is the ultimate goal of my game?
        • Is that goal clear to players?
        • If there is a series of goals, do the players understand that?
        • Are the different goals related to each other in a meaningful way?
        • Are my goals concrete, achievable, and rewarding?
        • Do I have a good balance of short- and long-term goals?
        • Do players have a chance to decide on their own goals?
    • Lens #26: The Lens of Rules
      • Look deep – most basic structure
      • Questions:
        • What are the foundational rules of my game? How do these differ from the operational rules?
        • Are there “laws” or “house rules” that are forming as the game develops? Should these be incorporated into my game directly?
        • Are there different modes in my game? Do these modes make things simpler, or more complex? Would the game be better with fewer modes? More modes?
        • Who enforces the rules?
        • Are the rules easy to understand, or is there confusion about them? If there is confusion, should I fix it by changing the rules or by explaining them more clearly?
    • Game design/invention process
      • Operational rules
      • Foundational rules
      • Written rules (end)
  • Mechanic 5: Skill
    • Skills
      • Physical Skills
      • Mental Skills
      • Social Skills
    • Real vs. Virtual
      • Player vs. Character
    • Enumerating Skills
    • Lens #27: The Lens of Skill
      • Look at the skills asked of players.
      • Questions:
        • What skills does my game require from the player?
        • Are there categories of skill that this game is missing?
        • Which skills are dominant?
        • Are these skills creating the experience I want?
        • Are some players much better at these skills than others? Does this make the game feel unfair?
        • Can players improve their skills with practice?
        • Does this game demand the right level of skill?


Engineering Education – Week 1.2 – Class Notes

In this second meeting we talked a bit about the landscape of online learning and about our final project group formation. I posted the idea of my Master’s project as an option and it got traction. Looks like the team will be Rodrigo (MBA/MSX), James (LDT), and Camila (LDT). Will be a great opportunity to evolve and focus the project.

Engineering Education – Week 1 – Reading Summary


  1. 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.
  2. Nathan, M. J., & Wagner Alibali, M. (2010). Learning sciences. Wiley Interdisciplinary Reviews: Cognitive Science, 1(3), 329-345.


I was very pleased to learn more about what Learning Sciences are. It is a profoundly interdisciplinary field and vast in reach that seem to strive for a culmination of several theories, research methods, design approaches, and implementation strategies. The readings provided me with a cognitively cohesive way of looking at all that I am learning over these past two quarters at LDT. The field proposes to look at both the macro and the micro, providing a common thread and a more holistic approach to education.

Furthermore, the shift in focus of the definition of learning from something a teacher does to a student towards something that the learner does themselves, provides a new lens to both research questions, design approaches, and instructional strategies. If the field could come up with a truly generalizable framework that would help teachers share knowledge, it could benefit the society as a whole. If we are able to understand how to better share knowledge, everyone can potentially become a teacher or a knowledge disseminator. The technology is available, but are the methods aligned with our society’s new way of communicating and interacting with each other?

Finally, the biggest takeaway from the readings was that our current theories of learning or cognition are still not easily transferable to a teacher’s everyday practice. Inline with bridging the gap between research and practice, providing tools for teachers to better carry out their mission is extremely important. My personal interests lie in this arena of using research findings to better aid instructors when creating online courses. I always feel that instead of blank templates available on LMSs, the tool itself could interact with the instructor directly in order to provide scaffolds, techniques, and suggestions for creating better learning experiences.

Engineering Education – Week 1 – Reading Notes

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.

  • Opening Quote:
    • Learning depends solely on the student. Teacher only influences what the student does to learn.
    • “Learning results from what the student does and thinks and only from what the student does and thinks. The teacher can advance learning only by influencing what the student does to learn.” (Ambrose et al, 2010, p.1)
  • Research and practice
    • “Instructors need a bridge between research and practice, between teaching and learning.” (Ambrose et al, 2010, p.4)
  • Common thread for student learning
    • Why certain teaching approaches are or are not supporting students’ learning?
    • Generate or refine teaching approaches and strategies that more effectively foster student learning in specific contexts.
    • Transfer and apply these principles to new courses.
  • What is learning?
    • A process that leads to change
      • Learning is a process, not a product. But can only be measured from products or performances
      • Involves long-term change of knowledge, beliefs, behaviors, or attitudes
      • Not done to students, rather something they do themselves
  • Principles of Learning
    • Students’ prior knowledge can help or hinder learning
    • How students organize knowledge influences how they learn and apply what they know.
    • Students’ motivation determines, directs, and sustains what they do to learn.
    • To develop mastery, students must acquire component skills, practice integrating them, and know when to apply what they have learned.
    • Goal-directed practice coupled with targeted feedback enhances the quality of students’ learning.
    • Students’ current level of development interacts with the social, emotional, and intellectual climate of the course to impact learning.
    • To become self-directed learners, students must learn to monitor and adjust their approaches to learning.
  • Generic principles
    • Domain-independent
    • Experience-independent
    • Cross-culturally relevant

Mental Notes:

  • Generalizable framework for learning is very useful especially now that anyone can become a teacher, share knowledge, or explain situations more clearly. Communication is education.

Nathan, M. J., & Wagner Alibali, M. (2010). Learning sciences. Wiley Interdisciplinary Reviews: Cognitive Science, 1(3), 329-345.

  • Learning Sciences’ main themes
    • Bridging the Divide between Research and Practice
    • Limitations of Theories of Learning to Prescribe and Assess Instruction
    • Analyzing and Assessing Interventions Using Experimental and Design-Based Approaches
    • Addressing Learning and Behavior of the Individual in Interaction
  • Methods
    • From macro to micro
    • Scale-up than scale down
    • Systemic approach to complement elemental approach
  • Multidisciplinary
    • Cognitive
    • Developmental psychology
    • Educational psychology
    • Education
    • Computer science
    • Neuroscience
    • Anthropology
    • Social linguistics
    • Sociology
  • Eduneering
    • design, implement, evaluate, and redesign innovative learning approaches and tools
  • LS – Learning Sciences
    • Modern and Postmodern views of human behavior
      • Postmodernists base on ‘Critical Theory’ where they critique and change society, rather than explain it
        • Looks at assumptions and implications on a larger context
    • Constructivism and socio-cultural theory
    • Cognitive science rejected behaviorist’s reduction of mental events to observed phenomena
      • “In LS, postmodern influences are apparent in basic theoretical constructs: knowledge is sometimes viewed from the epistemology of social and radical constructivism and its situated and distributed nature is emphasized; learning is framed as changes in discourse and participation within communities, and as problem-based and project-based; and transfer is recast as preparation for future learning and in agent-centered terms that address the perceptual and conceptual generalizations constructed by the learner rather than from the viewpoint of the domain expert.” (Nathan & Wagner, 2010, p.2)
  • Bridging the Divide between Research and Practice
    • From artificial to authentic settings
    • “Incompatibilities between research and practice can be framed as a mismatch between levels of granularity of the phenomena of interest.” (Nathan & Wagner, 2010, p.3)
    • Teachers, the main beneficiaries of cognitive theories, need to learn how to apply these concepts.
  • Limitations of Theories of Learning to Prescribe and Assess Instruction
    • Elemental studies provide great frameworks but are limiting when applied to authentic settings
      • “The general point is that, on its own, an elemental approach to the study of learning faces enormous challenges of scaling up when the scientific work is called upon for application to authentic settings.” (Nathan & Wagner, 2010, p.4)
    • Has to scale up and down – from students to national policy levels
    • All have to be involved and collaborate
  • Analyzing and Assessing Interventions Using Experimental and Design-Based Approaches (eduneering)
    • Experimental designs: control groups and random assignments
      • Internal validity and causal inference
      • Low ecological validity – unnatural adaptation of tasks
      • Looking at a limited set of variables – could be missing something important
    • Design oriented philosophy (engineering design)
      • “Expanded tool kit of data collection and analysis methods” (Nathan & Wagner, 2010, p.5)
      • “Design-based research provides for flexibility of interventions and faster means of innovation—similar to what Koedinger [p. 8] refers to as ‘the hare of intuitive design’—which can be complementary to the incremental approach of experimental research—Koedinger’s ‘tortoise of cumulative science’.“ (Nathan & Wagner, 2010, p.5)
  • Addressing Learning and Behavior of the Individual in Interaction (in interaction)
    • Context and setting
    • Affordances of objects in the world
    • Embodied knowledge grounded in experiences in the physical world
    • Knowledge distributed among members of a group and tools
    • Social interactions, including shared objects and representations
    • Positioning within the participation structure
    • Shared intentionality and intersubjectivity
    • Cultural, ethnic, and class influences
  • Time scales of human behavior
    • 10 ms: biological (primarily neural)
    • 100 ms to 10s: cognitive band: perceptual and motor processes: word and object recognition to brief communicative exchanges.
    • Minutes to hours: planful, interpersonal and task oriented
    • Hours to days: social and developmental operations, classroom or on-the-job training
    • Months and beyond: organizational, developmental, generational, and cultural terms
  • Trans-scale research

Mental Notes:

  • Learning Science is profoundly interdisciplinary and vast in reach. Culmination of theories, research methods, design approaches, and implementation strategies.