Game/Mobile Design internship at the AMNH (11/16 to 12/15)

(Mondays–9:30am to 4:00pm–and Wednesdays–9:30am to 5:00pm; plus work at home)

Total hours for this period (with holidays and sick days subtracted): 53

During this period the NND program shifted fully into its design phase. These are the Bootcamp Bootleg cards we ended up considering/using/adapting: cards for Sessions 17-21

As I mentioned in my last internship post, some of the observation work–and related activities–we had students doing yielded some good and interesting results. One of these observation-related activities, a “POV Madlib,” yielded enough that Barry thought it worthy of a post on his blog! (Psyched and honored was/am I. Though, it should be noted, the last couple of pictures and paragraphs were added by Barry, who thought to tie the post about the Madlib to some of the other observation-related activities). Here ’tis:

“People need a change in lighting because they walk to the right” – Using Design-based Learning with Museum Teens

And I’ve got another one to do next week!


Game/Mobile Design internship at the AMNH (10/16 to 11/15)

(Mondays–9:30am to 4:00pm–and Wednesdays–9:30am to 5:00pm; plus work at home)

Total hours for this period (with holidays and sick days subtracted): 52

As the Neanderthal Next Door (NND) program moved closer and closer to the design phase of the course, the principle work I did was on selecting from and adapting the Bootcamp Bootleg deck of design thinking cards.

The cards I ended up selecting and adapting (through 10/16) are in this document: cards for Sessions 9-16

Some of the language/elements/details in the adapted text in this document was altered again for the final curriculum documents (depending on feedback from Barry and other members of the team, on syllabus adjustments that needed to be made on the fly, etc.), but most of what’s here we ended up trying out. Ultimately I found this work very worthwhile–not only did I actually get to work with the cards “in the field,” but adapting these cards for use in the program–and altering them again in response to team feedback and to session-t0-session changes in the curriculum–was, I think, the largest chunk of curriculum design work I’ve ever done.

Nearly all the card activities we implemented during this period related to students doing user observations in the space they were designing for–the AMNH’s Hall of Human Origins. As with all the activities with the NND program, it was much easier to get some students more interested in these observations than others, but the results, even if not everything I’d/we’d hope they’d be, still yielded some interesting and useful stuff. But more on that in the next post…



Plass and Kaplan, “Emotional Design in Digital Media for Learning”

Plass and Kaplan state that the goals of their chapter are to

(1) review basic concepts related to emotion and learning, (2) summarize research on emotional design in digital media for learning, (3) present a theoretical framework of learning from digital media that emphasizes the need to consider emotional design factors in addition to cognitive design factors when designing multimedia learning materials, and (4) develop a research agenda for the study of emotional design for multimedia learning. (p. 1)

A substantial portion of Plass and Kaplan’s discussion in pursuit of these goals involves their argument that emotional or affective considerations should complement cognitive considerations when designing genuinely effective multimedia learning material. Such an approach, they note, that diverges from more traditional multimedia design for learning, which often ignored or minimized the affective in favor of the cognitive. Cognition and emotion, they note, are “inherently interconnected,” and “[t]his interconnectedness is an essential aspect of the complexity of human consciousness” (p. 1).

The interconnected relationship between emotion and cognition is a dynamic one, wherein “dynamic cognition-emotion interactions… emerge and operate in ways that are highly contextualized (and hence sensitive to contextual factors)” (p. 22). These interactions, Plass and Kaplan conclude, “serve as motivating forces that guide human adaptation and learning in specific contexts” (p. 22).

Knez and Neidenthal, “Lighting in Digital Game Worlds: Effects on Affect and Play Performance”

In their 2008 article, Knez and Neidenthal state that their study on lighting in digital game worlds “was designed to investigate the impact of warm (reddish) and cool (bluish) simulated illumination in digital game worlds on game users’ affect and play performance” (p. 129). They sought to compare these impacts with similar impacts (on affect and performance) observed in “real-world” environments. psychological effects of such lighting in “real-world” environments. What Knez and Deidenthal found was that users playing in digital worlds

performed best and fastest in a game world lit with a warm (reddish) as compared to a cool (bluish) lighting. The former color of lighting also induced the highest level of pleasantness in game users. A regression analysis indicated tentatively that it was the level of pleasantness induced by the warm lighting that enhanced the players’ better performance in that digital game world. (p. 129)

One of the things I found interesting about this article was a point that initially felt counter-intuitive to me, but quickly made a great deal of sense and left me wanting to investigate the subject. As Knez and Neidenthal note,

high-skilled players were…much more precise in their digital game taste than were the medium- and low-skilled players were. They played only the FPS (first person shooter) and RPG (role playing game) types of games (80% vs. 20%), while the medium- and low-skilled players played FPS, RPG, RTS (real-time strategy), action, sports, adventure, consol[e], music, hearts, MMORPG, Sim, and puzzle types of games. (p. 133)

What (point or process) causes a gamer’s shift from imprecise to precise tastes is one that I suspect the commercial games industry has investigated thoroughly. But has the educational games industry done the same? And why exactly are medium- and lower-skilled players more varied in their tastes? Are the reasons few or many?

Picard, Affective Computing, Chapter 1

In this chapter Picard frames her discussion with what she—and most others—see as the two primary aspects of human emotion—the physical an the cognitive. Within—and across (as the distinctions between “physical” and “cognitive” are far from clear-cut)—these two aspects Picard explores particular features of human emotion (or “emotion theory”) she feels are important to consider in order to create genuinely affective computing, to give  computers “the ability to recognize, express, and ‘have’ emotions” (p. 44). These features are “social display rules, universal vs. person-specific responses, primary vs. secondary emotions, the role of emotions in creativity and general memory processes, the existence of multiple paths for emotion expression in humans, and emotion inducement” (p. 44).

Picard also spends some time highlighting ways in which “emotion can be expressed through sentic modulation—including facial expression, vocal intonation, gesture, posture, and other bodily changes” (p. 44). “Sentic modulation,” in turn, are expressions “such as voice inflection, facial expression, and posture,” are “the physical means by which an emotional state is typically expressed, and is the primary means of communicating human emotion” (p. 25).

One of the things I found particularly interesting about this chapter is Picard’s consideration of computers’ “recognition problem”—wherein they have (or at least had, at the time of the book’s publishing) difficulty recognizing, or focusing-in on and interpreting, human speech acts and meaning under certain circumstances. She argues for a

“universal” recognizer… [that] would first ask “Which category is this person most similar to?” In speech, this might be likened to asking “who sounds like this—both accent-wise and voice-quality wise?” Subsequently, a recognizer can be used that was trained on the prototype person for that category. A benefit of this approach is that it is also likely to reveal categories of affective expression that theorists have not yet identified. (p. 34)

I’d never thought of such a problem before, and it leaves me wondering what kind of recognition systems currently exist, and how much they do or don’t resemble such a kind as Picard describes.

Picard, Affective Computing, Introduction

In the Introduction to Affective Computing (1997), Picard overviews and sets up her argument for the book, stating that it “proposes that we give computers the ability to recognize, express, and in some cases, ‘have’ emotions” (p. 1). She proposes this because, she contends (after raising and critiquing various points that might be made against such a proposal), “[a]fter nearly a half century of research … computer scientists have not succeeded in constructing a machine that can reason intelligently about difficult problems or that can interact intelligently with people” (p. 1). Picard further sketches the outlines of the book as “lay[ing] a foundation and construct[ing] a framework for what I call ‘affective computing,’ computing that relates to, arises from, or deliberately influences emotions” (p. 3).

Much of the rest of the Introduction is devoted to Picard making the case for (simply put) emotional intelligence—both as a vital element in human cognitive functioning (including decision-making, a subject she spends some time on here) and as a form of intelligence we should strive to create for and in computers. “[C]omputers,” she argues, “if they are to be truly effective at decision making, will have to have emotions or emotion-like mechanisms working in concert with their rule-based systems” (p. 12).

One of the things that struck me about Picard’s argument in the Introduction is this phrase, “emotion-like mechanisms.” At this—early—point in her book, I can’t decide whether her offering it is a compromised position (from computers having “real” emotions or emotional capabilities) or not, whether it seems to come somewhat too soon or somewhat too late in her argument, even though it’s only a dozen pages into the book.

Evolutionary tree and speciation games–yes, fun! (But who has the time?)

A couple of weeks into my internship, Hannah asked if I could take a quick-ish look into what games and/or simulations we could use in the program session on evolutionary trees–how to make them, what they tell you, etc. This is what I was able to come up with for her:

Hi Hannah,


Unfortunately, I haven’t found all that much good and/or interesting digital stuff out there so far. Seems like card games might be the best bet. Anyway—

If this (digital option) actually seems worthwhile, might we be able to get our hands on it somehow?—

(reviewed here, as part of a suite, apparently:)

This card game is a little more on the gaming-intensive side, takes 45-60 minutes (apparently), and is for a slightly older audience (10+):
Terra Evolution: Tree of Life

This card game (a Kickstarter-funded thing) doesn’t come out until November, is more for middle school and up (8+), takes less time to play (I’m assuming), but might be a little closer to what you’re looking to do in the session:
Go Extinct! Go Fish…evolved (Maybe worth looking at the press kit they provide the link for here?)

And maybe there’s something to be related/taught with this online puzzler?—

The following day (that I was in the museum) she asked if I could look into games about speciation (which I did have to look up to make sure I thoroughly understood). Didn’t have to twist my arm to look for more good (or at least decent games):

Hi Hannah,

Here’s what I’ve been able to find (that looks halfway decent) so far.
(Currently in Alpha. Pretty sure Windows-only. Gameplay probably takes awhile.)
(Gameplay probably shorter.)
(Complex gameplay that takes a long time. Site lists 3 hours. Does look to get good reviews, though.)

One of the challenges of this program is how little time there actually is with the students–to help/get them to learn things. Three hours a session twice a week isn’t all that much, really, especially given all the content this program is looking for them to be exposed to. And we don’t/can’t really assign them homework (mostly because students are very unlikely to do it on a regular basis). So, this means that it’s highly unlikely that students would be able to spend any significant amount of time on any of the games that are genuinely educational, because these games (like most things) require a significant time investment in order to really get anything out of the experience.

Looking into augmented reality for Neanderthals

The first sizable project Barry has had me working on is looking into what augmented reality (AR) apps we could demo for the students, to give them a sense of what’s possible, of what design considerations they’ll eventually have to start thinking about. My responsibilities also included adjusting the curriculum for the “Intro to augmented reality” session accordingly (as we used the curriculum from a prior Youth Initiatives program that incorporated AR as a template) and co-facilitating (or teaching) that part of the session itself. (Sessions for the students are on Mondays and Wednesdays from 1:15pm to 4:15pm.)

The final list we came up with was the following–the majority of the apps were taken from the curriculum for the previous Youth Initiatives program, and a couple were suggested by the Sackler lab staffers working on The Neanderthal Next Door, but a couple of them I was able to discover and make the case for through my research:

In the “Intro to augmented reality” itself, students were most interested in and impressed by Anatomy 4D and (being New Yorkers) by Tunnel Vision.

My research on this piece of the program actually helped me solidify my thinking about, and come to more of a decision about, my capstone project. And, it turns out, the primary technology I’m planning on using, Augmented Reality Interactive Storytelling (ARIS) mobile platform, is one that Barry knows quite well.

Game/Mobile Design internship at the AMNH (9/15 to 10/15)

(Mondays–9:30am to 4:00pm–and Wednesdays–9:30am to 5:00pm)

Total hours for this period (with holidays and sick days subtracted): 56

The vast majority of my time at the American Museum of Natural History (AMNH) has been and will be devoted to a program conducted by the museum’s Education Department, entitled “The Neanderthal Next Door.”  The program describes itself as follows:


The Neanderthal Next Door” is a new, 27-session youth program for 21 12th-graders designed to develop and implement a digitally augmented (augmented reality-enhanced) print activity guide that explores the topic of human evolution through the frame of Neanderthals. The guide will be used by visitors to the The Sackler Educational Laboratory for Comparative Genomics and Human Origins and the Hall of Human Origins (HHO). After the prototype for the guide is developed, eight of the participating youth will become interns who—working in pairs on weekends, twice a month—will facilitate the learning experience for museum visitors using the guide.

Educational Objectives of the Augmented Activity Guide:

People who participate in the guide will be able to:

  • increase their understanding of the topic of human evolution through the lens of Neanderthals, including:
    • evolutionary theory,
    • history of paleoanthropological discoveries
    • comparative skeletal anatomy,
    • comparative genomics
    • fossil discoveries, and
    • cultural artifacts,
    • appreciate how and why scientists collect data to understand the human evolutionary story, and
    • engage in a deeper level of inquiry with a museum exhibit.

Educational Objectives of the Youth Program:

In addition to the educational objectives of the activity guide, youth developing it in the after school program will also be able to:

  • understand general knowledge about key biological and cultural shifts throughout the evolution of our own species;
  • understand museum exhibits as dynamic learning environments;
  • co-design a hall-based educational experience;
  • think critically about what specific aspects of human evolution inspire the greatest curiosity among visitors;
  • contribute to the museum’s knowledge of how to integrate new digital tools into exhibit-based experiences that create new pathways for visitor engagement; and
  • expand their 21st Century Learning Skills, like collaboration, evidence-based thinking, and visualization;

For those youth participating in the internship, they will also be able to:

  • recruit museum visitors to engage with an augmented activity guide;
  • use an augmented activity guide to facilitate learning experiences; and
  • collect and interpret evaluation data on a prototype.

As the Game/Mobile Design intern, my primary role in the “Neanderthal Next Door” program is working on (or, rather, working with students as they work on) the augmented reality piece of the activity guide. (This piece will actually be developed, after prototyping and testing has happened with the smaller group of 12th-grade interns next term, by a company the Digital Learning department has worked with previously, Geomedia.) The primary person I have been and will be working with in this role is my supervisor, Barry Joseph, Associate Director For Digital Learning, Youth Initiatives at AMNH. Barry’s bio from the Games for Change website reads, in part:

He has developed innovative programs in the areas of youth-led online dialogues, video games as a form of youth media, the application of social networks for social good, the educational potential of virtual worlds like Second Life, the educational application of mobile phones and alternative assessments models, and more, always seeking to combine youth development practices with the development of high profile digital media projects that develop 21st Century Skills and New Media Literacies. Barry speaks frequently around the country at conferences and leads professional development trainings for a wide variety of educational, civic and cultural institutions and published articles in a wide variety of publications. He is one of the co-founders of Games For Change.

The other staffer I have been and will be working more closely with is Hannah Jaris, a scientist and STEM educator by training, who is the Senior Coordinator for Digital Learning and Youth Initiatives. One of the things I’ve been able to learn more about with and from Hannah is curriculum design, which is something I need more training in.

Other duties for the internship so far have included some document processing (i.e. creating documents in/for the program’s shared Google Drive, formatting them, synching them with other documents, etc.) and the occasional task related to other Digital Learning projects Barry is currently working on.

Chapter 3, Rules of Play (Salen and Zimmerman)

In this Chapter, Salen and Zimmerman explore a definition of “meaningful play,” which they see as—and emphasize should be—the goal of successful game design. “There are two ways to define meaningful play,” they note—“descriptive and evaluative,” wherein “[t]he descriptive definition addresses the mechanism by which all games create meaning through play” and “[t]he evaluative definition helps us understand why some games provide more meaningful play than others “(p. 55).(1) “Meaningful play in a game,” their descriptive definition states, “emerges from the relationship between player action and system outcome; it is the process by which a player takes action within the designed system of a game and the system responds to the action. The meaning of an action in a game resides in the relationship between action and outcome” (p. 55). Their evaluative definition further states: “[m]eaningful play is what occurs when the relationships between actions and outcomes in a game are both discernible and integrated into the larger context of the game,” where “[d]iscernability means that a player can perceive the immediate outcome of an action,” and “[i]ntegration means that the outcome of an action is woven into the game system as a whole” (p. 55).

My instinct, when considering educational games in relation to these definitions, was to say that the evaluative definition was much more important. On second thought, however—not only is it vital that one take the descriptive definition seriously, so that its (poor) design doesn’t distract from the more evaluative-related design of the game, of the learning one is trying engender; but, if done well enough, these more descriptive elements can also aid learning. Perhaps an analogous argument is that the best musical scores in cinema are those that are nearly invisible enhancements to the film, that are so well integrated from the visual that the two elements work as one.

(1) Please note: All page number references are from the DAISY text version of Rules of Play.