Thinking Fast and Slow

Thinking Fast and Slow is a book by Daniel Kahneman.  Kahneman is an Israeli American psychologist who won the Nobel Prize in Economics in 2002 for his work on judgement and decision-making.  The book is a fascinating tour of our own mind, how we think slowly and delibrately, and how we make fast decisions, and the faults and biases of both ways of thinking.  The TED talk introduction credits him as being "widely regarded as the world's most influential living psychologist.."

We don’t choose between experiences, we choose between memories of experiences. Even when we think about the future, we don’t think of our future normally as experiences. We think of our future as anticipated memories.” (Daniel Kahneman)

Daniel_KAHNEMAN.jpg ‎(150 × 179 pixels, file size: 49 KB, MIME type: image/jpeg)

Daniel_KAHNEMAN.jpg ‎(150 × 179 pixels, file size: 49 KB, MIME type: image/jpeg) from the Wikimedia Commons

•Daniel Kahneman: The riddle of experience vs. memory TED talk
http://www.ted.com/talks/daniel_kahneman_the_riddle_of_experience_vs_memory.htmhttp://www.ted.com/talks/daniel_kahneman_the_riddle_of_experience_vs_memory.htmll
•YouTube TIME 10 Questions for Noel Laureate Daniel Kahneman
http://www.youtube.com/watch?v=l4zSc2lYl60http://www.youtube.com/watch?v=l4zSc2lYl60
•Video with Charlie Rose on his book, Thinking Fast and Thinking Slow
http://www.charlierose.com/view/interview/12185http://www.charlierose.com/view/interview/12185
(you need to register and login to see the video)

US Science Education: Teacher Preparation

Eric Plutzer, a political science professor at Penn State University, has found that 28 percent of high school biology teachers do a good job of teaching evolution and are comfortable with the subject, while 13 percent do not believe in Darwinian evolution and often won't teach it.
That leaves a broad group of nearly 60 percent of teachers who accept the concepts of evolution but are wary of dealing with critics in their communities, Mr. Plutzer said. As a result, they often tell their students they have to teach evolution because it's part of the state standards, "but everyone is free to believe what they want."

USA Today seems content with the US "doing fine in science education".

References
•Roth, M., Why does the US Fail at Science Education? Pittsburgh Post-Gazette, March 29, 2012, Retrieved on September 26, 2012 from w.post-gazette.com/stories/news/us/why-does-us-fail-in-science-education-287936/.
•

Carl Weiman: Effective Teaching Should Create Students Who Think Like Scientists

Carl Weiman is Physics Nobelist for the production, in 1995 with Eric Allin Cornell, of the first true Bose–Einstein condensate.

In 2007 Wieman joined the University of British Columbia to head a well-endowed science education initiative.  He is active speaking out for STEM education, inquiry teaching, and a definite change in traditional science teaching habits.  Weiman is instrumental in organizing the Celebrate Science at the 3rd USA Science and Engineering Festival to be held in Washington, D.C. in April 2014. http://www.usasciencefestival.org/about/advisorshttp://www.usasciencefestival.org/about/advisors


References
•Carl Weiman: http://computinged.wordpress.com/2012/06/15/carl-wieman-on-effective-teaching/ or on YouTube: http://www.youtube.com/watch?v=_TUHobGNdbM Science Magazine, A Better Way to Teach?
•Donley, Elizabeth A.; Neil R. Claussen; Simon L. Cornish; Jacob L. Roberts; Eric A. Cornell; Carl E. Wieman (2001-07-19). "Dynamics of Collapsing and Exploding Bose−Einstein Condensates". Nature 412 (6844): 295–299. arXiv:cond-mat/0105019. Bibcode 2001Natur.412..295D. doi:10.1038/35085500. PMID 11460153.
•http://nobelprize.org/nobel_prizes/physics/laureates/2001/public.html
•"CU-Boulder Nobel Laureate Carl Wieman Announces Move To British Columbia, Will Remain Linked To CU-Boulder" (Press release). University of Colorado, Boulder. 2006-03-20.

Connected Educator Month, August 2012

 The American Institutes for Research (AIR) coordinated the Connected Educator Month for the US Department of Education.

According to AIR Senior Researcher Darren Cambridge, his organization also expects to produce a publication "to identify some of the key themes, to get a sense of the scope of what happened, and if there are implications for policy and for the fields going forward, to try to articulate those too."

 The event consisted on multitudes of online organizations holding webinars, virtual panels,chats, discussion forums, book clubs, galleries, exhibits, and broadcasts.  One can find recordings made of the activities at connectededucators.org.  The organizer, lead researcher, Darren Cambridge would like to run the event again next year.  Archives for the keynote videos are available at: http://connectededucators.org/cem/cem-kickoff/http://connectededucators.org/cem/cem-kickoff/.

It sounds like a great event but the problem is that the organizers don't know how many people participated and there is no way for these people to get back in touch with each other unless they all go to each individual site again.  Wouldn't it be better if they had joined all of this activity into the OU's Educational Futures community and people could maintain contacts and connections?

CEM Update @ PLP Live

Project director Darren Cambridge joins thought leaders John Seely Brown, Will Richardson, and Sheryl Nussbaum-Beach in sharing learnings from CEM at PLP Live, Sept. 28!

Reference
Schaffhauser, Dian, Connected Educator Month Brings Teachers, Others Together Online, THE Journal, 9/26/12. Accessed September 26, 2012 at: http://thejournal.com/Articles/2012/09/26/Connected-Educator-Month-Brings-Teachers-Others-Together-Online.aspx?=THE21&p=1

Network Awareness Tool

Network Awareness Tool - Learning Analytics in the workplace: 
Detecting and Analyzing Informal Workplace Learning from maarten de laat

Contested Collective Intelligence

Contested Collective Intelligence: Resilience, Complexity & Sensemaking from Simon Buckingham Shum

Collective Intelligence

Collective Intelligence for OER Sustainability from Simon Buckingham Shum

Educational Futures Hub

Educational Futures Evidence Hub from Simon Buckingham Shum

Enquiry Blogger

enquiryblogger-analytics-calrg2012 from Simon Buckingham Shum

Our Learning Analytics are Our Pedagogy SBS

Our Learning Analytics are Our Pedagogy from Simon Buckingham Shum

Learning Analytics Infographic from Open College, Sydney

To see this infographic minus the overlay on this blog's table of contents, please go to:
http://newsroom.opencolleges.edu.au/learning-analytics-infographic/http://newsroom.opencolleges.edu.au/learning-analytics-infographic/
Dont forget the last what can it do? relates to creating better learning environments for students to learn--social learning analytics.  Ferguson and Buckingham Shum have identified 5 social learning analytics--I will post more.

Add caption

State of Science Education in California 2012

California teachers lack the resources and time to teach science, LA Times, October 31, 2011

Math and Science Teacher Initiative, CSU

Teach California

The Center for the Future of Teaching and Learning at WestEd

Untapped Potential:Science Education from CFTL (Center for the Future of Teaching and Learning)

This is from CFTL:

Untapped Potential: The Status of Middle School Science Education in California

Untapped Potential: The Status of Middle School Science Education in California finds that the state's middle schools have the potential to provide students with high quality science education, but significant challenges limit opportunities for science learning, leaving that potential unfulfilled.  This statewide study of science education shows that middle schools offer dedicated time for science, access to facilities and a teaching force that is fairly well prepared for teaching the subject. But students often lack access to science instruction in earlier grades and arrive at middle school unprepared and uninterested. Systemic support for science has eroded and overcrowded classrooms, insufficient time for instruction and inadequate resources limit access to high quality learning opportunities.
The research shows that:

• nearly 40 percent of teachers view students' lack of interest as a major or moderate challenge to science instruction.
• nearly half (47%) of principals report students' lack of preparation as a major or moderate challenge.
• nearly one-quarter of middle school teachers may not have an adequate background or preparation for teaching the subject.
• nearly 60 percent of surveyed teachers identified insufficient professional development as a barrier to high-quality science instruction.
• just 14 percent of middle school teachers provide a pattern of classroom practices that support regular engagement of students in the practices of science.

The full report Untapped Potential is available at:
http://www.cftl.org/Whats__New.htm#16

Also are articles on:

Lost Opportunities: The Status of Science Education in California Middle Schools

High Hopes – Few Opportunities

 

 

Manhattan Beach iPad Program: About and News

Manhattan Beach iPad Program

FYI about the program

Approved APS

1:1 Program
Teacher Interviews

Files:

•  iPad Cost Summary _Read-Only_.pdf
•  MBMS Parent iPad Information Night.pdf
•  MBUSD iPad Pilot Board Update _1.pdf
•  MBUSD iPad Pilot Board Update _2.pdf
•  MBUSD iPad Pilot Board Update_3.pdf 

 About the program:

http://www.easyreadernews.com/46222/manhattan-beach-unified-ipad-pilot/

http://www.dailybreeze.com/news/ci_21048125/manhattan-beach-middle-school-students-all-will-be?source=rss

http://www.dailybreeze.com/news/ci_21121621/renee-moilanen-manhattan-beach-school-looks-future-its

http://blogs.laweekly.com/informer/2012/07/ipad_all_students_manhattan_beach_middle_school.php

http://robkuznia.com/ipad-craze-hits-south-bay-schools

http://www.scpr.org/blogs/education/2012/06/01/6304/school-plan-outfit-students-tablet-computers-encou/

http://manhattanbeach.patch.com/articles/school-district-begins-rolling-out-ipads

http://www.mbmswaves.com/content/mbms-ipads-important-update

http://www.ipadinschools.com/328/largest-deployment-of-ipads-in-schools/

Ed Futures Hub, part of the OU Evidence Hub

 Evidence Hub http://edfutures.evidence-hub.net/
about the future of learning and technology
ideal one for me to put my work into the ed futures
OPEN ed if want to work on
continuing to develop ed futures hub--
demo movies hub-about how do we involve children and young people in research, example content,
this is a version of cohere (open ended knowledge mapping tool, slightly scary and have to think in semantic triples-cocnep evidence to claim node type claim and support-some like this, some don't)  the evidence hub uses the
 XIP may be working in the background of the evidence hub instead of cohere--when you add a report or a claim--now XIP could quicklyu scan it to evaluate the claims it is making
in dialogue with potential test bed users-whjat is a coherent research plan, and what is practical to go with

http://evidence-hub.nethttp://ci.olnet.orghttp://rcyp.evidence-hub.net/
sign up here and click on add to add supportingevidence,  what you are doing is creating a semantic link, but don't really know you are doing that-the semantic network is hidden, once you've signed in you can just add a resource, a bit more familiar and less mappy, a simpler user interface, a simplified application of the cohere concept
      interests in the link types
     interest from professional developers, who thinks they have a solution to different problems, who is trying different approaches, pull up a google map of the city, and see what is being done
     interest from teacher trainers-- build a collective intelligence website
or require training teachers to share what they know about ie using tech approaches in the classroom

Ed Futures Hub  http://edfutures.evidence-hub.net/
need an invite to sign up -- ask Simon
this is meant to be a hub that connects the OUs research with teachers, policy makers, we need a place for researchers, policy makers, and vendors--teachers who can benefit--provide a neutral place for all to discuss-driver, a place for those who want to understand evidence based policy
could be useful -- value a neutral space to talk to teachers and look at evidence base
OU trying to have better quality conversations
training teachers at UCLA, UCI or Stanford (or the New Teacher Center)--all CA education

build in to a student--you haven't contributed any  or generate analytics resports that
start adding in analytics--useful pedagogically
we need new ways of connecting our schools and our teachers with each other--evaluate the analytics

find a client and community--then Anna DeLiddo, lead researcher w Simon, helps them understand how it works, and starts to create things to make a demo--take to the wider community--around relevant material--bring up google map, know these schools had an interesting results, get the bug, my role of community facilitator in my hub
send link  can you see uses here as a learning platform for students or for teacher trainers to share more structured results--slightly more structured-the system can give you more useful feedback--can follow people or a particular challenge that you want to keep up with.

see the different building blocks, get weekly or monthly digest--
California schools-certain problems, ESL, science teaching --
we would talk through different use phases, bring up the map for the city, the state, whose working on what, click on google map markers and see how we would use this--we have a problem knowing who is working on what--when people see it they usually get a response quickly
send it to people and show demos--
  UCI-Sue Marshall
  UCLA-Megan Franke, Noel Enyedy, Sharon Sutton,

start with a shell for California, only creat a hub dedicated to science teachers professional development--join Ed Futures Hub and have CA be a part of the whole--more oportunistic connections may be made, UK with US teachers,
future of learning and technology
me as OU researcher--putting into
Open Ed Hub
built hub with the Hewlett Foundation, build up shells with different communities


http://technologies.kmi.open.ac.uk/cohere/2012/01/09/cohere-plus-automated-rhetorical-annotation/
http://evidence-hub.nethttp://ci.olnet.orghttp://rcyp.evidence-hub.net/
http://rcyp.evidence-hub.net/explore.php?id=137108145210781268001337251487
http://edfutures.evidence-hub.net/http://ci.olnet.org/#org-orggmap

Teacher Change and Social Learning Theory

 To scaffold teacher inclusion of scientific discourse and inquiry inclusion in their practice, according to social learning theory they must:

1. Attention – in order for an individual to learn something, they must pay attention to the features of the modeled behavior.
2. Retention – humans need to be able to remember details of the behaviour in order to learn and later reproduce the behavior.
3. Reproduction – in reproducing a behavior, an individual must organize his or her responses in accordance with the model behavior. This ability can improve with practice.
4. Motivation – there must be an incentive or motivation driving the individual’s reproduction of the behaviour. Even if all of the above factors are present, the person will not engage in the behaviour without motivation.

Julian Rotter suggests that the effect of one's behavior impacts people's desire to engage in that behavior, prefering positive results to negative.  His take on social learning theory says that one's behavior is not just influenced by social modeling and connection, but also by environmental factors.

References
•Rotter, J.B. (1954). Social Learning and Clinical Psychology. Prentice-Hall
•Bandura, A. (1977). Social Learning Theory. General Learning Press.
•The Social Learning Theory of Julian B. Rotter

Learning Analytics and Social Learning Analytics and References

Social Learning Analytics

• Ferguson, R. and Buckingham Shum, S. (2012) Social Learning Analytics: Five Approaches, Proc. 2nd International Conference on Learning Analytics & Knowledge, 29 Apr-2 May, Vancouver, BC
• Buckingham Shum, S., Cannavacciuolo, L., De Liddo, A., Iandoli, L. and Quinto, I. (2011) Using Social network Analysis to Support Collective Decision-Making Process, International Journal of Decision Support System Technology, 3, 2, pp. 15-31, IGI Global
  •Ferguson, R. and Buckingham Shum, S. (2011) Learning Analytics To Identify Exploratory Dialogue within Synchronous Text Chat, Learning Analytics and Knowledge 2011, Banff, Canada
  Buckingham Shum, S. and Ferguson, R. (2010) Towards a social learning space for open educational resources, OpenED2010: Seventh Annual Open Education Conference, Barcelona, Spain
  De Liddo, A. and Buckingham Shum, S. (2010) Capturing and Representing Deliberation in Participatory Planning Practices, International Conference on Online Deliberation (OD2010), Leeds, UK
  
  
  Quinto, I., Buckingham Shum, S., De Liddo, A. and Iandoli, L. (2010) A Debate Dashboard to Enhance On-Line Knowledge Sharing, Proceedings 5th International Forum on Knowledge Asset Dynamics (Intellectual Capital in a Complex Business Landscape), June 24-26, Matera, Italy
  
  
  Quinto, I., Buckingham Shum, S., De Liddo, A. and Iandoli, L. (2010) A Debate Dashboard to Enhance On-Line Knowledge Sharing, IFKAD Conference - Intellectual Capital in a Complex Business Landscape, Matera Italy
  
  
  Selvin, A., Buckingham Shum, S. and Aakhus, M. (2010) The Practice Level in Participatory Design Rationale: Studying Practitioner Moves and Choices, Human Technology: An Interdisciplinary Journal on Humans in ICT Environments. Special Issue on Creativity and Rationale in Software Design, 6, 1, pp. 71-105
  
  

Social Learning Theories and References

Socially Distributed Cognition (Hutchins, 1995)
     how connectionist ideas could be applied to social systems. 

• Hutchins, E. (1995) "How a cockpit remembers its speeds". Cognitive Science, 19, 265-288.
• Hutchins, Edwin (1995). Cognition in the Wild. MIT Press. ISBN 0-262-58146-9.
• Pea, R. D. (1993). Practices of distributed intelligence and designs for education. In G. Salomon (Ed.). Distributed cognitions (pp. 47-87). New York: Cambridge University Press.

Activity theory (Vygotsky, Leont’ev, Luria, and others starting in the 1920s)
       proposed that people are socio-culturally embedded actors, with learning considered using three features – involving a subject (the learner), an object (the task or activity) and tool or mediating artifacts

• Bedny, Gregory; Meister, David (1997). The Russian Theory of Activity: Current Applications To Design and Learning. Series in Applied Psychology. Psychology Press. ISBN 978-0-8058-1771-3.
• Engeström, Yrjö; Miettinen, Reijo; Punamäki, Raija-Leena (1999). Perspectives on Activity Theory. Cambridge University Press. ISBN 0-521-43730-X.

Social cognitive theory (Bandura, 1962)
     assumption that people learn by watching what others do which was elaborated further in social learning theory

• Bandura, Albert (1976). Social Learning Theory. Englewood Cliffs, NJ: Prentice Hall. ISBN 978-0138167448
• Bandura, Albert (1985). Social Foundations of Thought and Action. Englewood Cliffs, NJ: Prentice-Hall. ISBN 978-0138156145
• "Albert Bandura Bobo Doll Experiment: A Study of Aggression." YouTube, Web. 29 Mar. 2010
• "Albert Bandura speaking at Everett M. Rogers Award Colloquium 2007" YouTube, (1h33

 Social learning theory (Miller and Dollard).

• Miller, N. & Dollard, J. (1941). Social Learning and Imitation. Yale University Press.

Situated cognition (Brown, Collins, & Duguid, 1989; Greeno & Moore, 1993)
     all knowledge is situated in activity bound to social, cultural and physical contexts; knowledge and learning that requires thinking on the fly rather than the storage and retrieval of conceptual knowledge.

•  Brown, J. S.; Collins, A. & Duguid, S. (1989). "Situated cognition and the culture of learning". Educational Researcher 18 (1): 32–42.
• Greeno, J. G. (1989). "A perspective on thinking". American Psychologist 44 (2): 134–141. doi:10.1037/0003-066X.44.2.134.
• Greeno, J. G. (1994). "Gibson's affordances". Psychological Review 101 (2): 336–342. doi:10.1037/0033-295X.101.2.336. PMID 8022965.
• Greeno, J. G. (1998). "The situativity of knowing, learning, and research". American Psychologist 53 (1): 5–26. doi:10.1037/0003-066X.53.1.5.
• Greeno, J. G. (2006). "Authoritative, accountable positioning and connected, general knowing: Progressive themes in understanding transfer". J. of the Learning Sciences 15 (4): 539–550.
• Kirshner, D. & Whitson, J. A. (1997) Situated Cognition: Social, semiotic, and psychological perspectives. Mahwah, NJ: Erlbaum (ISBN 0-8058-2038-8) 
• Kirshner, D.; Whitson, J. A. (1998). "Obstacles to understanding cognition as situated". Educational Researcher 27 (8): 22–28. doi:10.3102/0013189X027008022. JSTOR 1177113.

Community of practice (Lave & Wenger 1991)
     through the process of sharing information and experiences with the group that the members learn from each other, and have an opportunity to develop themselves personally and professionally.

• Lave, Jean; Wenger, Etienne (1991). Situated Learning: Legitimate Peripheral Participation. Cambridge: Cambridge University Press. ISBN 0-521-42374-0.; first published in 1990 as Institute for Research on Learning report 90-0013
• Wenger, Etienne (1998). Communities of Practice: Learning, Meaning, and Identity. Cambridge: Cambridge University Press. ISBN 978-0-521-66363-2.
• Wenger, Etienne; McDermott, Richard; Snyder, William M. (2002). Cultivating Communities of Practice (Hardcover). Harvard Business Press; 1 edition. ISBN 978-1-57851-330-7.
•  Kimble, Chris; Hildreth, Paul; Bourdon, Isabelle (2008). Communities of Practice: Creating Learning Environments for Educators. Information Age Publishing. ISBN 1-59311-863-5.

Collective intelligence (Lévy, 1994).

•  Hofstadter, Douglas (1979). Gödel, Escher, Bach: an Eternal Golden Braid. New York: Basic Books.
• Leimeister, Jan Marco (2010). Collective IntelligenceCollective.
• Riedl, Christoph; Blohm, Ivo; Leimeister, Jan Marco; Krcmar, Helmut (2010). RATING SCALES FOR COLLECTIVE INTELLIGENCE IN INNOVATION COMMUNITIES: WHY QUICK AND EASY DECISION MAKING DOES NOT GET IT RIGHT
•  Brown, J.S. et al.  The Power of Pull
• The New Social Learning 
• De Liddo, A., Sándor, Á. and Buckingham Shum, S. (2012) Contested Collective Intelligence: Rationale, Technologies, and a Human-Machine Annotation Study, Computer Supported Cooperative Work  slideshare: http://www.slideshare.net/sbs/kmiolnetparc20110401http://www.slideshare.net/sbs/kmiolnetparc20110401
  •De Liddo, A., Buckingham Shum, S., McAndrew, P. and Farrow, R. (2012) The Open Education Evidence Hub: A Collective Intelligence Tool for Evidence Based Policy, Cambridge 2012: Joint OER12 and OpenCourseWare Consortium Global 2012 Conference, Cambridge, UK 
  •Buckingham Shum, S., Cannavacciuolo, L., De Liddo, A., Iandoli, L. and Quinto, I. (2011) Using Social network Analysis to Support Collective Decision-Making Process, International Journal of Decision Support System Technology, 3, 2, pp. 15-31, IGI Global
  •Buckingham Shum, S. and De Liddo, A. (2010) Collective Intelligence for OER Sustainability, OpenED2010: Seventh Annual Open Education Conference, Barcelona, Spain
  •De Liddo, A. and Buckingham Shum, S. (2010) Cohere: A Prototype for Contested Collective Intelligence, Workshop: Collective Intelligence In Organizations - Toward a Research Agenda at ACM Computer Supported Cooperative Work (CSCW 2010), Savannah, Georgia, USA 

Connectivist Learning Theory

Connectivism is a theory of learning which espouses that knowledge exists in the world, not in the individual.  The individual, therefore, must make connections, social connections, to learn.  The building of connections by making intelligent social networking choises and keeping involved in maintaining these connections allows for the co-creation  of knowledge in our global, networked world.

Connectivism is similar to Vygotsky's activity theory in perceiving knowledge as existing in systems which people access through participation.  Similarity to Bandura's Social Learning Theory is that people learn by being in contact.  Connectivism emphasizes the role of technology on the way learners learn within network systems, including social networking.  Verhagen disputes the idea that connectivism is actually a learning theory, and instead calls it a perspective on learning.

...Socially Distributed Cognition (Hutchins, 1995), which explored how connectionist ideas could be applied to social systems. But also other theories that adhere to more classical views of cognition. The Activity theory (Vygotsky, Leont’ev, Luria, and others starting in the 1920s) that proposed that people are socio-culturally embedded actors, with learning considered using three features – involving a subject (the learner), an object (the task or activity) and tool or mediating artefacts. The Social cognitive theory (Bandura, 1962) and the assumption that people learn by watching what others do which was elaborated further in the Social learning theory (Miller and Dollard). The notion of Situated cognition (Brown, Collins, & Duguid, 1989; Greeno & Moore, 1993), that all knowledge is situated in activity bound to social, cultural and physical contexts; knowledge and learning that requires thinking on the fly rather than the storage and retrieval of conceptual knowledge. The concept of Community of practice (Lave & Wenger 1991) - it is through the process of sharing information and experiences with the group that the members learn from each other, and have an opportunity to develop themselves personally and professionally. Or even the idea of Collective intelligence (Lévy, 1994). (http://en.wikipedia.org/wiki/Connectivism)

Principles of connectivism

• Learning and knowledge rests in diversity of opinions.
• Learning is a process of connecting specialized nodes or information sources.
• Learning may reside in non-human appliances.
• Capacity to know more is more critical than what is currently known
• Nurturing and maintaining connections is needed to facilitate continual learning.
• Ability to see connections between fields, ideas, and concepts is a core skill.
• Currency (accurate, up-to-date knowledge) is the intent of all connectivist learning activities.
• Decision-making is itself a learning process. Choosing what to learn and the meaning of incoming information is seen through the lens of a shifting reality. While there is a right answer now, it may be wrong tomorrow due to alterations in the information climate affecting the decision. (http://en.wikipedia.org/wiki/Connectivism)

References
•Siemens, G. (2004). Connectivism: A Learning Theory for the Digital Age, International Journal of Instructional Technology and Distance Learning, Vol. 2 No. 1, Jan 2005. Retrieved September 11, 2012, from http://www.elearnspace.org/Articles/connectivism.htm
•Siemens, G. (2005). Connectivism: Learning as Network-Creation, Learning Circuits, November 2005, Retrieved    , from http://www.elearnspace.org/Articles/networks.htm
•Siemens, G. (2006). Knowing Knowledge. Retrieved December 24, 2008, from
http://ltc.umanitoba.ca/KnowingKnowledge/index.php/Main_Page
•Siemens, G. (2008). Learning and Knowing in Networks: Changing Roles for Educators and Designers. Retrieved December 27, 2008, from http://it.coe.uga.edu/itforum/Paper105/Siemens.pdf
•Siemens, G. (2008). Complexity, Chaos, and Emergence. Retrieved February 23, 2009, from http://docs.google.com/Doc?id=anw8wkk6fjc_15cfmrctf8
•Siemens, G. (2008). New structures and spaces of learning: The systemic impact of connective knowledge, connectivism, and networked learning. Retrieved December 10, 2008, from http://elearnspace.org/Articles/systemic_impact.htm
•Connectivism: a new learning theory?, Pløn Verhagen (University of Twente), November 2009
•Connectivism: Learning as Network-Creation, Learning Circuits, November 2005
•Downes, Stephen. "What Connectivism Is". Retrieved 2009-01-28.
•Siemens, George; Stephen Downes. "Connectivism and Connective Knowledge". Retrieved 2009-01-28.
•Siemens, George. "MOOC or Mega-Connectivism Course". Retrieved 2009-01-28.

Grounded theory 1

Grounded theory research is mainly used in qualitative research, and works in reverse from most traditional social science research.  Grounding theory began to be used in Human Computer Interaction research, and was then brought into the Computer Supported Collaborative Learning (CSCL) community, which is now part of the International Society of the Learning Sciences (ICLS).  It is now used more widely in learning sciences research.

The first step is data collection, then coding the key points of the data with codes and extracting them from the text.  Codes are grouped as concepts, and then categories are formed. The categories becomes the basis for the creation of a theory, or the hypothesis of the experiement in retrospect.
Traditionally, a researcher chooses their theoretical framework and applies it to the research.

Barney Glaser and Anselm Strauss developed the grounded theory method.


References
•Baker, M., Hansen, T., Joiner, R. & Traum, D. (1999). The role of grounding in
collaborative learning tasks. In P. Dillenbourg (Ed.), Collaborative learning:
Cognitive and computational approaches (pp. 31-63). Amsterdam: Pergamon /
Elsevier Science. [34 pages]

readings about grounding theory:
Anderson, A. H. (2006). Achieving understanding in face-to-face and video-mediated
multiparty interactions. Discourse Processes, 41(3), 251-287. Finally a paper looking at
how groups of three or larger ground their understanding!
Bangerter, A. & Clark, H. H. (2003). Navigating joint projects with dialogue. Cognitive
Science, 27(2), 195-225. This is the most recent piece on the idea that people also ‘ground’
what it is that they are doing together at the level of “joint projects”, which build upon
conversational contributions. This piece focuses on markers of transitions between and
within joint projects. However, the best piece introducing joint projects is Chapter 7 in
Clark (1996) below.
Clark, H. H. (1996). Using language. Cambridge, UK: Cambridge University Press. This is the
comprehensive source about all aspects of grounding theory, which are put in relationship
to each other here. Key chapters to check out include: Chapter 6 about multimodal
signaling, and Chapter 7 about joint projects, the last of which is online.
Clark, H. H. and Brennan, S. B. (1991). Grounding in communication. In L. B. Resnick, J. M.
Levine & S. D. Teasley (Eds.), Perspectives on socially shared cognition (pp. 127-149).
Washington, DC: American Psychological Association. [23 pages] Focuses on how
grounding changes depending on medium and purpose. Very relevant for those interested
in technology-mediated communication or for thinking about how interactions change
depending on what people are trying to do together.
Schober, M. F. & Brennan, S. E. (2003). Processes of interactive spoken discourse: The role of
the partner. In A. C. Graesser, M. A. Gernsbacher & S. R. Goldman (Eds.), Handbook of
discourse processes (pp. 123-164). Mahwah, NJ: Erlbaum [42 pages]. This review article,
written years later by two of Clark’s former students and editors of the journal Discourse
Processes, gets into the issue of what it means for an interaction to be interactive, and all the
controversies that have arisen about that.

readings on applications of grounding theory to education:
Beers, P., Kirschner, P. A., Boshuizen, H. P. A. & Gijselaers W. H. (2007). ICT-support for
grounding in the classroom. Instructional Science, 35, 535-556. [22 pages] A more recent
application of grounding theory to CSCL focused on designing classroom systems to support
more effective grounding.
Fong, C. (2007, March). Identity issues in ESL chat rooms: Grounding positioning statements in
Linguistics Colloquium, Cornell University, Ithaca, NY. This revision of Carlton’s course
paper from the fall 2006 Discourse and Learning seminar applies Clark’s idea of joint
projects to analyze identity negotiations in an ESL chat room.
Rummel, N. & Spada, H. (2005). Learning to collaborate: An instructional approach to
promoting collaborative problem solving in computer-mediated settings. Journal of the
Learning Sciences, 14(2), 201-241. [41 pages]

Niels Bohr: Knowledge and Practice of Science

The task of science is both to extend our experience and reduce it to order, and this
task represents various aspects, inseparably connected with each other. Only by
experience itself do we come to recognize those laws which grant us a
comprehensive view of the diversity of phenomena. As our knowledge becomes
wider we must always be prepared, therefore, to expect alterations in the points of
view best suited for the ordering of our experience.
--Niels Bohr

Bohr describes scientific knowledge as including the experience itself and that scientific practices extend our experiences of the natural world to order, or to understanding and changing our points of view.  School science is not often the experience described by Bohr, but has been distilled by textbooks that rarely present the experiences of science.  Textbooks give the conclusions of the studies of different scientist without showing their data, or giving students a chance to view or hear their arguments.  The data collection and pattern-finding of scientists is rarely explored, and often reduced to a series of explanations, graphs, charts, and maps.  The textbook study of science diverges completely from the experience of scientists' science.

Purpose

Through this  study, a major purpose is development social  learning analytics to scaffold teachers’ scientific own discourse development and teaching practice changes that embrace scientific discourse and inquiry.

New technologies can help

New advanced technologies can assist teachers in communicating with their students effectively to make students’ thinking visible, and to provide tailored feedback to meet specific student needs (NRC, 2004; Owens, Irving, Pape, Abrahamson, & Sanalan, 2007; Pape, Owens, & Irving, 2008; Roschelle, Penuel, & Abrahamson, 2004).

Studies on teacher to student feedback do not focus on specific aspects of learning science, such as argumentation and discourse skills. 

(Duschl & Gitomer, 1997; Nystrand & Gamoran, 1991; Webb, Nemer, & Ing, 2006; Windschitl et al., 2008).

More coming
 learning analytics
cohere
discourse


References
•Owens, D. T., Irving, K. E., Pape, S., Abrahamson, L., & Sanalan, V. A. (2007). The connected classroom: Implementation and research trial. In C. Montgomerie & J. Seale (Eds.), Proceedings of the ED-MEDIA World Conference on Educational Multimedia, Hypermedia & Telecommunications. Chesapeake, VA: Association for the Advancement of Computing in Education (AACE).
•Pape, S. J., Owens, D. T., & Irving, K. E. (2008). Classroom connectivity in promoting algebra 1 & Physical Science achievement and self-regulated learning: Year 1 results. Paper presented at the the 2008 IES Research Conference, Washington, DC.
•Roschelle, J., Penuel, W. R., & Abrahamson, L. (2004). The networked classroom. Educational Leadership, 61(5), 50-54.
 •Duschl, R. A., & Gitomer, D. H. (1997). Strategies and challenges to changing the focus of assessment and instruction in science classrooms. Educational Assessment, 4(1), 37-73.
•Nystrand, M., & Gamoran, A. (1991). Instructional discourse, student engagement, and literature achievement. Research in the Teaching of English, 25(3), 261-290.
•Windschitl, M., Thompson, J., & Braaten, M. (2008). How novice science teachers appropriate epistemic discourses around model-based inquiry for use in classrooms. Cognition and Instruction, 26(3), 310 - 378.

•Webb, N. M., Nemer, K. M., & Ing, M. (2006). Small-group reflections: Parallels between teacher discourse and student behavior in peer-directed groups. Journal of the Learning Sciences, 15(1), 63-119.
•

Teach Scientific Discourse

Gee describes discourse (1991, p.3):

a socially accepted association among ways of using language, of thinking, and of acting that can be used to identify oneself as a member of a socially meaningful group or “social network”…Think of discourse as an “identity kit” which comes complete with the appropriate costume and instructions on how to act and talk so as to take a particular role that others will recognize.

How do teachers teach scientific discourse?
In order to teach science, teachers need to understand pedagogical science knowledge that includes understanding science content, inquiry processes, how children learn, developmental understandings, and skills for facilitating classroom experiences to support active inquiry and conceptual development.
warning of the state of science education in the United States for children at all grade levels (Grigg, Lauko, & Brockway, 2006)
US children underperform in science achievement when compared to students in other countries (Gonzales, Guzmán, Partelow, Pahlke, Jocelyn, Kastberg, & Williams, 2004)
naïve ideas about science phenomena they bring with them to kindergarten frequently survive unchanged through high school and even college (Bishop & Anderson, 1990; Schneps & Sadler, 1988)
to be considered “fully proficient in science” (Duschl, Schweingruber, & Shouse, 2007), they must be able to (1) know, use, and interpret scientific explanations; (2) generate and evaluate scientific evidence and explanations; (3) understand the nature and development of scientific knowledge; and (4) participate productively in scientific practices and discourse (Duschl et al., 2007).
It is now widely known that cognitive stimulation in the early years is critical for brain development and that young children have cognitive capacities far beyond what was previously believed (Shonkoff & Phillips, 2000)

The Importance of Promoting the Growth of All Students

To provide quality science education for all students, NSTA recommends that science educators

• show respect for each individual and value his or her identity and cultural heritage;
• recognize the abilities and strengths of students, as well as their unique learning needs (NBPTS 1999);
• model and emphasize the skills, attitudes, and values of scientific inquiry (NRC 1996);
• help students reflect as learners and use skills of inquiry to become effective problem solvers ( NSTA 2004);
• display and demand respect for diverse ideas, skills, and experiences of all students (NRC 1996);
• structure and facilitate ongoing formal and informal discussion based on a shared understanding of rules of scientific discourse (NRC 1996); and
• orchestrate discourse among students about scientific ideas (NRC 1996).

References
•Duschl, Richard A.; Schweingruber, Heidi A.; & Shouse, Andrew W. (Eds.). (2007). Taking science to school: Learning and teaching science in grades K-8. Washington, DC: National Academies Press.
•Gonzales, Patrick; Guzmán Juan Carlos; Partelow, Lisette; Pahlke, Erin; Jocelyn, Leslie; Kastberg, David; & Williams, Trevor. (2004). Highlights from the Trends in International Mathematics and Sciences Study: TIMSS 2003 (NCES 2005-005). Washington, DC: U.S. Department of Education, National Center for Education Statistics. Retrieved August 27, 2008, from http://nces.ed.gov/pubsearch/pubsinfo.asp?pubid=2005005
•Loucks-Horsley, Susan; Hewson, Peter W.; Love, Nancy; & Stiles, Katherine E. (1998). Designing professional development for teachers of science and mathematics. Thousand Oaks, CA: Corwin Press.
•Snow-Renner, Ravay, & Lauer, Patricia A. (2005). Professional development analysis. Denver, CO: McREL.
•Wenglinsky, Harold; & Silverstein, Samuel C. (2006). The science training teachers need. Educational Leadership, 64(4), 24-29.
•Garet, Michael S.; Porter, Andrew C.; Desimone, Laura; Birman, Beatrice F.; & Yoon, Kwang Suk. (2001). What makes professional development effective? Results from a national sample of teachers. American Educational Research Journal, 38(4), 915-945.
•Grigg, Wendy S.; Lauko, Mary A.; & Brockway, Debra M. (2006). The nation’s report card: Science 2005 (NCES 2006-466). Washington, DC: U.S. Department of Education, National Center for Education Statistics. Retrieved August 27, 2008, from http://nces.ed.gov/nationsreportcard/pdf/main2005/2006466.pdf
•Nelson, J.R. & Stage, S.A., "Fostering the development of vocabulary knowledge and reading comprehension though contextually-based multiple meaning vocabulary instruction," Education and Treatment of Children 30, 1 (2007): 1–22.
•Lemke, J.L., Talking science: Language, learning, and values, (Norwood, NJ: Ablex Publishing, 1990).
•Abd-El-Khalick, F. & Lederman, N.G., "Improving science teachers’ conceptions of the nature of science: A critical review of the literature," International Journal of Science Education 22,7 (200): 665-701.
•Gee, J. P. (2004). Discourse analysis: What makes it critical? In R. Rogers (Ed.), An introduction to critical discourse analysis in education (pp. 19-50). London: Routledge.
•Gee, J. P. (2010). An introduction to discourse analysis: Theory and method (3rd ed.). New York, NY: Routledge.

Lack of scientific discourse in science education

The problem: Lack of Discourse skills in science education

Science education goals and method of instruction includes participation in scientific discourse.  The Board on Science Education (BOSE) states that scientific argumentation and explanations are part of student experience  to aid their understanding and discourse skills in the science classroom. (NRC, 2007)  Scientific discourse is emphasized in the National Science Education Standards (NSES), and the role of the teacher in the classroom is critical to enhance student understanding through discourse.   Language is used in the teaching of science to communicate the learning, the details of the structure of lessons and experiments, but also as a way to learn to speak as scientists do to each other.  Science talk in the classroom helps to explain, to analyze, to describe, to compare, to record, to ask questions, to brainstorm what conclusions mean, to evaluate and to make and  test hypotheses about the natural world.  (Wellington & Osborne, 2001) Classroom discourse, student feedback and formative assessment have all been recent topics of learning sciences educational research in science education (Gee, 2010; Hattie & Timperley, 2007; Lemke, 1998; Shute, 2008; Windschitl et al., 2008). 

However, in spite of attempts to reform science education, many teachers of science do not incorporate discourse into their teaching.  Teachers are still noted to be doing most of the talking in science classes, trying to "deliver" science knowledge to students.  In trying to meet all of the science objectives, teachers may rarely ask students to share their thinking about phenomena, or to help students formulate ways of talking about science.  Much of the classroom dialogue still involves teacher questioning students for the correct answer, rather than elaborating on their thinking, or asking new questions.  

-->

(Duschl, Schweingruber, & Shouse, 2007; Hardy, Kloetzer, Moeller, & Sodian, 2010; Windschitl, Thompson, & Braaten, 2008). Teachers with teacher-dominant discourse styles tend to persuade their students that the scientific knowledge presented is indeed valid.  These teachers have little opportunity or time to improve their own or their students discourse abilities.

-->

(Black & Wiliam, 1998; Hicks, 1996; NRC, 2007).

Some researchers and academics credit teacher lack of understanding of benefits of formative feedback, while being more concerned with summative processes.  

--> (Black & Wiliam, 1998; Kluger & DeNisi, 1998; Shute, 2008)   Others recognize that especially elementary teachers may have little science content knowledge and may not have acquired their own scientific discourse skills, much less be able to communicate and create the environment of true science talk.   --> (Hardy et al., 2010; Windschitl et al., 2008; Zimmerman, 2007). 

References

•Gee, J. P. (2010). An introduction to discourse analysis: Theory and method (3rd ed.). New York, NY: Routledge.

•Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81-112.

•Lemke, J. L. (1998). Talking science: Language, learning, and values. Westport, CT: Ablex Publishing Corporation.

•Shute, V. J. (2008). Focus on formative feedback. Review of Educational Research, 78(1), 153-189.

•Windschitl, M., Thompson, J., & Braaten, M. (2008). How novice science teachers appropriate epistemic discourses around model-based inquiry for use in classrooms. Cognition and Instruction, 26(3), 310 - 378.

•Duschl, R. A., Schweingruber, H. A., & Shouse, A. W. (Eds.). (2007). Taking science to school: Learning and teaching science in grades K-8. Washington, DC: National Academy Press.

•Hardy, I., Kloetzer, B., Moeller, K., & Sodian, B. (2010). The analysis of classroom discourse: Elementary school science curricula advancing reasoning with evidence. Educational Assessment, 15(3), 197-221.

•Black, P., & Wiliam, D. (1998). Assessment and classroom learning. Assessment in Education, 5(1), 7-74.

•Kluger, A. N., & DeNisi, A. (1998). Feedback interventions: Toward the understanding of a double-edged sword. Current Directions in Psychological Science, 7(3), 67-72.

•Zimmerman, C. (2007). The development of scientific thinking skills in elementary and middle school. Developmental Review, 27(2), 172-223.

•Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Cambridge, MA: Harvard Univ Press.

•WEllington, J., Osborne, J., Language and Literacy in Science Education, Open University Press, Buckingham, Philadelphia, 2001.

•BOSE, NRC, 2007

Science Teaching and rating scale (STERS)

From:
Chalufour, Ingrid; Worth, Karen; & Clark-Chiarelli, Nancy. (2003). Science teaching and environment rating scale. Unpublished manuscript.Science Teaching Environment Rating Scale (STERS) (Chalufour, Worth, & Clark-Chiarelli, 2003)

• The STERS uses a four-point scale (1 = inadequate, 2 = partial, 3 = adequate, and 4 = exemplary)
• Evaluated whether teacher participants at the three geographical field sites:
  • Created creative learning Environment
  • Facilitates direct experiences to promote conceptual learning
  • Promotes the use of scientific inquiry
  • Plans in-depth investigations.
  • Reliability and validity of the STERS is being studied at this time by the developers at the Education Development Center.
  • All of the classrooms in the pilot study (N = 19) and a sample of the classrooms in the field test (18 out of 23) were observed by the external evaluator.

Findings

Results indicate that teachers were able to implement R&P successfully (see Table 1).
Table 1: Science Teaching Environment Rating Scale (STERS) Results

STERS subscale	Inadequate (1)	Partial (2)	Adequate (3)	Exemplary (4)	Mean
Environment	--	8% (3)	51% (19)	41% (15)	3.36
Facilitates	--	22% (8)	32% (12)	46% (17)	3.21
Facilitates	--	22% (8)	32% (12)	46% (17)	3.21
Promotes	--	24% (9)	41% (15)	35% (13)	3.06
Plans	--	16% (6)	32% (12)	51% (19)	3.31

---

Designing Interface Studies you can learn from

"do you like my interface?"  -- not very specific, giving a lickert scale, this is useful, agree/disagree, and there is a please the experimenter bias.
Developers are valuable testers.  Being the developer and the tester can be valuable. 
Getting beyond "do you like my interface?"

What's the comparison?
What's the yardstick?
When measuring effectiveness, even informally, good to have some comparison. 
Start out with a baserate question: how often does Y occur? requires mesuring Y
Correlations: Do x and y co-vary
requires measuring x and y
Causes: does x cause Y?
requires measuring x and y, and manipulating x
also requires somehow accounting for the effects of other independent variables

manipulations
independent variables--- indepenend of what the user does, in control of the experimenter
measures
dependent variables--what the user does measured-task completion time, create an acoount
accuracy, how many mistakes, how much do they remember afterwards, how do they feel emotionally afterward
precision
internal validity-if you ran it again, would you see the same results, to have a precise experiement you need to be able to remove the confounding factors and study enough people

generalizability
external validity--does this apply only to certain age group, or all?

ASK: is my approach better than the industry standard?

challenge--compare new cool, fidelity of implementation, and the new approach, or some combination
how to tease apart causal factors? when is it more relevant? to decide between 2 cameras-image quality or usability may be less relevant.  when you are a designer, you do have control over the variables
benefits and drawbacks of the QWERTY keyboard -iphone
manipulation; input style
measure-words per minute
however, imp to realize that it is important to realize that old phone users are expert at their older devices, to not be used to something the first time, may not be important. 
IS THIS DIFFERENCE SIGNIFICANT?
authors of user centric study-- did another study-- found that QWQERTY and iphone were about the same-- same speed, but iphone make many more errors.  however, in 2007, may have different kinds of people if you used different people for both comparison pieces of the study--potential for variation is greater.

strategies for fairer comparisons
insert your new approach into the production setting
recreate the production approach in your new setting
scale things down so you're just looking at a piece of a larger system
when expertise is relevant, train people up (give them the practice they need)

IS INTERFACE X BETTER THAN INTERFACE Y?
what dfoes better mean? in a complex system, several measures needed.  wht are you trying to improve, the answer is mostly it depends, and what does it depend on-gets to the goal of the interface, for what???
controlled comparison enables causal inference  (you can learn from what is causal to make a better decision going forward-

Distributing Cognition with user interface

User interfaces can help people distribute their cognitive load.  Interfaces can
encourage participation, scaffold learning, show differences that matter, or only differences that matter, convert slow calculations to fast perceptions of the idea, support chunking, increase efficiency, and facilitate collaboration. 
Tetris, study done by David Kirsh, UCSD, research on players.  Moving and rotating pieces on the screen may seem like a waste of time--people actually move the block more than they actually need to, but as you become an expert, Kirsh found that experts relied more heavily on the cognitive effort of moving things in the world--became a bigger task. 

From the learning sciences, the Montessori blocks give representations for numbers as physical estanciations.  Can the transparent representations scaffold learning, by making things concrete. 
These are good examples of the power of representation.  Good representations show all the relevant information, with nothing extra.  They enable comparison, exploration, and problem-solving.  They should enable the kinds of tasks users would like to do. 
London underground subway map--first map to abstract the layout of the map from the physical geography.  The Underground map designers realized that the common task of riders is to get from a to b.  The physical details were more information than they needed and made the task more difficult.  The detail was stripped down, making it easier to get between connections.  They also represented the distances far away as less relevant, the suburban areas were squished into the map.  For someone aming decisions of where to get off, or the compromise with the distance between stations.  You might believe that  Nearly all representation design is about fitness to task. According to the London Underground map, a good representation is tight to the task the user wants to perform.

Temperature map from the WEather Underground.  The temp is drawn right on the place where the temp exists.  What are good or bad problems?  If you want to know what the temp is along the coast, and don't care about town, this gives good information.  Or, it gives good information about general temperature.  Every temperature is shown identity, so you need to scan.  If the temp color or size would correspnd to the weather,
Edward Tufte books on color and design.
The depoth below sea level is represented by ROYGBIV.  this is not an ordering of colors, it is substitutive, we don't automatically have a more or less than value for color, so the individual chunks of a depth pop out.  The yellow pops out.  If you are trying to get the sense of the depth of the sea, what would be better to use color as a representational view.


His redesign:
Everything above sea level is brown, similar to real world.  the water is blue, and the intensity of the color changes with depth, the deeper blues are darker blues, which corresponds to our intuitions.  The idea that water by the shore is pale, this idea leverages that knowledge we all hold.

What makes a good representation is tied up with the task of the user and what the user's expertise is.

Chess- exemplar domain to understand== 1971 Chase and Simon
hypothesis-experts have memory for board, or have their ten thousand hours
experts are better at remembering the configuration of the board  ONLY if it is an actual game.  If you arrange the pieces on the board in a way you don't play chess.  This relates to the ability of experts to leverage their knowledge of the domain.
Chunking interfaces
ideally should make it easier -- interface designers can we make interfaces more chunkable and place a lower load on our memory.  Bill Buxton looked at moving test on locations on a document--keyboard shortcut to cut and paste--that is 3 different operations, and if interrupted, you might forget what is in the clipboard.  The pictures is worth 10,000 words.  should we represent information visually or textually.
It depends.  One time visually is more effective is when you can convert slow reasoning tasks into fast perception tasks by making them visually salient--London underground map and the good coloring map.  Tables of numbers-can be difficult to see trends, but visually including outliers becomes automatically visually salient.

Worth 10,000 words--interchange ability? how can we establish the informational equivalence.
informational equiv is not necessarily equal to computational equivalence. 

example
A pari of parallel lines is cut by a transversal. 
sentence and the picture are equivalent, but the pic requires less cognition

Distributing cognition for group work Ed Hussion on airplane cockpits
the artifacts in the cockpit help.  on landing and takeoff, the speed needs to be accruate-most important
plastic indicators called bugs around the indicators--to mark what events will cause a change in the wings, etc.  By making the triggers for what will make the action manifest to everybody, these artifacts can help increase collaboration and safety.

With DC interfaces can also increase efficiency using diagrams, and facilitate collaboration, as in the cockpits.

Poor representations are unfortunately common but can be deadly.  When you enter a password and are told that it is not valid.  It should tell you the requirements for the password the first time.  A message like you must fill out all fields is ineffective.  It might show only the parts you missed, or show the part you need to fill out.  If the information that is needed is not present, users get confused.  Ebay funding confirmation page, you will see if you switch to a credit card.  One option is pay with bank account and one is pay with credit card.  The bright one is pay with a bank account to encourage users to use this.  The other one looks like it is greyed out, but keeps users from having ebay pay their credit card fee.
In outlook, gives a duplicate contact detected,  To streamline the information, it can show the final information and what the changes will be.  Should show both old and new information in same format. 

Further reading
Don Norman, Things that make us smart
Ed Hutchins, Cognition in the Wild
Herb Simon, Sciences of the Artificial.