Difference between revisions of "EDUC 6470 Experimental Instructional Plans"

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See [[EDUC 6470 Possible Topics]] for the rest of the topics which I discarded after generating this one.
 
See [[EDUC 6470 Possible Topics]] for the rest of the topics which I discarded after generating this one.
  
 +
[[File:WindSpeedHistogram.jpg|400px|thumb|right|Wind speed histogram for a turbine in virtual world Second Life]]
 
===Siting a wind turbine===
 
===Siting a wind turbine===
[[File:WindSpeedHistogram.jpg|400px|thumb|right|Wind speed histogram for a turbine in virtual world Second Life]]
 
 
;Course:9-12th grade earth science
 
;Course:9-12th grade earth science
 
;Topic:Atmosphere and land.
 
;Topic:Atmosphere and land.
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##Students will discuss ideas with each other, but every student is responsible for their own mind map.
 
##Students will discuss ideas with each other, but every student is responsible for their own mind map.
 
##Students will be expected to raise questions about the data and what it means for siting a wind turbine advantageously for producing electricity. Some relevant considerations are planned for another class; if a student raises such a consideration, the instructor may ask the student to record the inquiry for the next class meeting.
 
##Students will be expected to raise questions about the data and what it means for siting a wind turbine advantageously for producing electricity. Some relevant considerations are planned for another class; if a student raises such a consideration, the instructor may ask the student to record the inquiry for the next class meeting.
 +
##Students can get help from the instructor in raising questions and figuring how to retrieve the necessary data.
 
#Whole class watches anemometer histogram being built for 5 minutes. (Will it be meaningful enough in that short time? Test.)
 
#Whole class watches anemometer histogram being built for 5 minutes. (Will it be meaningful enough in that short time? Test.)
 
#Class is given a data set and asked to generate questions to ask of the data. 10 minutes
 
#Class is given a data set and asked to generate questions to ask of the data. 10 minutes
 +
##Aggregate data can be retrieved as a wind rose or a directionless histogram of speeds from http://energyteachers.org/secondlife/winddata.php
 +
##Histograms of speeds at different sites can be viewed in Second Life.
 +
##Students can ask a MySQL for data aggregated however they like.
 
#Review mind maps, 4 minutes.
 
#Review mind maps, 4 minutes.
 
##Check for tentative concepts created/synthesized by students.
 
##Check for tentative concepts created/synthesized by students.
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*Learner directed toward areas and sources of scientific knowledge.
 
*Learner directed toward areas and sources of scientific knowledge.
 
*Learner forms reasonable and logical argument to communicate explanations.
 
*Learner forms reasonable and logical argument to communicate explanations.
 +
;Post-trial comments
 +
*Dealing with running Second Life may have slowed the introduction a bit.
 +
*Passing around a real, working anemometer at the beginning worked to quickly introduce each student to the idea of anemometry.
 +
*Ratings are summarized at [[File:PeerTeachingRatings.pdf]]. Looking at the ratings, I notice that it is especially hard to keep to a schedule when allowing students to come up with their own questions. The improper closure was uncomfortable both for the students and the instructor. So, I might try in the future to ease classes unfamiliar with freer inquiry, or use non-class time for closure (this sounds risky).
 +
*The students were completely unenthusiastic about choosing their own data to analyze. Perhaps a computer program or instruction sheet could help them by providing them with a limited number of choices at first.
 +
*We didn't meet the data-analysis objective. It is still unclear whether the students felt unprepared to make any analysis, or whether the whole class was hijacked by asking questions unnecessary to the objective. I am reminded of findings that unexperienced teachers find spend too much time explaining things. (reference?)
 +
*Because we didn't meet the data-analysis objective, we didn't try the crux of this lesson, and missed out on many of the measures of innovation. Here is a list of those I think we did manage to cover, noting that I think raters were too generous in rating the presence of "essential features of inquiry."
 +
#Instruction is situated in authentic tasks, authentic to the science as scientists do it, if not authentic to the students.
 +
#Students and teacher debate ideas and negotiate understanding, hopefully.
 +
#The planners are aware of both the degree of guidance and the degree of inquiry, acknowledging that these can be separate.
 +
#Students ask (are asked) how well do the data represent the phenomena for which they stand?
 +
#Learners pose their own questions. But also
 +
#Learners engage in question provided by teacher.
 +
#Learner directed toward areas and sources of scientific knowledge.
 +
#Learner forms reasonable and logical argument to communicate explanations.
 +
*I wonder if the freer inquiry is always going to feel less well-managed than the didactic classroom? On the other hand, I have had experiences, though rarely, where students asked the instructor to get out of the way so they could learn better.
  
;References:Brown et al., 2006, on what's missing from science courses.
+
;References:Brown et al., (Brown, P., Abell, S., & Demir, A. (2006). College science teachers’ views of classroom inquiry. Science Education, 90, (5), 784-802.) on what's missing from science courses.
 
:Measuring Wind Project at EnergyTeachers.org http://energyteachers.org/project_detail.php?project_id=4
 
:Measuring Wind Project at EnergyTeachers.org http://energyteachers.org/project_detail.php?project_id=4
 
:WeatherScope, Mesonet, Oklahoma Climatological Survey at http://www.mesonet.org/
 
:WeatherScope, Mesonet, Oklahoma Climatological Survey at http://www.mesonet.org/
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==Todo list==
 
==Todo list==
*Make a clearer histogram, showing units, maybe number of samples
+
*Make a clearer histogram, showing units, maybe number of samples.
*Make histogram start blank.
+
*Write a stand-alone program for answering queries of wind data, graphing.

Latest revision as of 13:38, 7 May 2010

Explanation

These plans are designed for trial in EDUC 6470, and may be developed for my future use.

For any of these lessons, I would like to focus on the tension between free inquiry and predetermined goals, as in Furtak 2006.

Optional concepts indicate the possibile learning outcomes depending on student or teacher choice of paths during the lesson.

Planning Group

A group of four in our class is collaborating on our plans: Joseph Ashong, Jeff King, Shawn Reeves, and Adi Md Sikin.

Joseph works in nutrition, Jeff in math, Adi in food processing, and I in high school physics.

Meetings

2010-03-03
We discussed our subjects, possible goals and concepts for our students.
2010-03-17
5:30-6:30 Duffield Hall:We explored the conceptual structures in our lessons.

Possible topics for the lesson

See EDUC 6470 Possible Topics for the rest of the topics which I discarded after generating this one.

Wind speed histogram for a turbine in virtual world Second Life

Siting a wind turbine

Course
9-12th grade earth science
Topic
Atmosphere and land.
Instructor
Shawn Reeves, physics and earth science teacher
Audience
9-12th grade students
Pre-context
This is the first class of the second term of an earth science class. During the previous term, students studied the radiation budget between sun-earth and earth-space. As part of that unit, students learned about solar power, renewables, solar cooking, climate change. They have never seen a histogram.
Post-context
We show students power curves for wind turbines. Students are asked to revise their inferences based on these power curves, which show that wind turbines have cut-in and cut-out speeds, and make about ten times as much power at 15m/s, a rare wind speed, than at 5m/s, a very common wind speed.
Activity
Given an anemometer and a wind vane, students explore a virtual world where wind is modeled. With the help of a data-facilitator, students ask questions of the data. Students then analyze the data on their own, then make inferences and reason why those inferences would be important to deciding where to site a wind turbine. Students are directed towards other sources for wind data, such as NOAA ASOS.
Activity Details for 20 minute trial lesson in EDUC 6470, April 21, 2010. See #Todo list for incomplete tasks
  1. Announce expectations, 1 minute.
    1. Each student will spend entire class building a mind map of concepts and connections discussed in class, either on paper or using CMap. Making links to existing structure is encouraged.
    2. Students will discuss ideas with each other, but every student is responsible for their own mind map.
    3. Students will be expected to raise questions about the data and what it means for siting a wind turbine advantageously for producing electricity. Some relevant considerations are planned for another class; if a student raises such a consideration, the instructor may ask the student to record the inquiry for the next class meeting.
    4. Students can get help from the instructor in raising questions and figuring how to retrieve the necessary data.
  2. Whole class watches anemometer histogram being built for 5 minutes. (Will it be meaningful enough in that short time? Test.)
  3. Class is given a data set and asked to generate questions to ask of the data. 10 minutes
    1. Aggregate data can be retrieved as a wind rose or a directionless histogram of speeds from http://energyteachers.org/secondlife/winddata.php
    2. Histograms of speeds at different sites can be viewed in Second Life.
    3. Students can ask a MySQL for data aggregated however they like.
  4. Review mind maps, 4 minutes.
    1. Check for tentative concepts created/synthesized by students.
    2. Check for tentative meanings assigned to distribution of directions and distribution of speeds.
  5. Offer list of sites to go next for more information
  6. Preview what we'll be doing next class--Looking at how a wind turbine generates different amounts of power at different wind speeds.
Driving question
How can we characterize wind so that we can predict wind power generation?
Concepts
wind speed, wind direction, compass, wind rose, histogram, statistics, prediction.
Goals
Students will present wind data that will help anyone understand whether a site will produce sufficient wind power.
Objectives
Students will create charts and or tables that clarify pertinent data. Students will organize data into sets that aren't too large to handle, nor too small to be meaningful.
Discussion
One of the more experimental methods of this lesson is the use of the "data-facilitator." The data-facilitator can be a student or instructor or aide who knows how to take an analytical question and turn it into a structured query, using the structured query language to most database programs. The instructor is going to need to measure the knowledge and skills the students bring to the course, specifically about histograms, statistics, the relationship between statistics and predictability, and the concept of speed.
Innovative teaching components, or explicit features of inquiry
  • Instruction is situated in authentic tasks, authentic to the science as scientists do it, if not authentic to the students.
  • Students and teacher debate ideas and negotiate understanding, hopefully.
  • The planners are aware of both the degree of guidance and the degree of inquiry, acknowledging that these can be separate.
  • Students ask (are asked) how well do the data represent the phenomena for which they stand?
  • Learners collect their choice of possible data.
  • Learners pose their own questions. But also
  • Learners engage in question provided by teacher.
  • Learner directed to collect certain data. But also
  • Learner told how to analyze.
  • Learner directed toward areas and sources of scientific knowledge.
  • Learner forms reasonable and logical argument to communicate explanations.
Post-trial comments
  • Dealing with running Second Life may have slowed the introduction a bit.
  • Passing around a real, working anemometer at the beginning worked to quickly introduce each student to the idea of anemometry.
  • Ratings are summarized at File:PeerTeachingRatings.pdf. Looking at the ratings, I notice that it is especially hard to keep to a schedule when allowing students to come up with their own questions. The improper closure was uncomfortable both for the students and the instructor. So, I might try in the future to ease classes unfamiliar with freer inquiry, or use non-class time for closure (this sounds risky).
  • The students were completely unenthusiastic about choosing their own data to analyze. Perhaps a computer program or instruction sheet could help them by providing them with a limited number of choices at first.
  • We didn't meet the data-analysis objective. It is still unclear whether the students felt unprepared to make any analysis, or whether the whole class was hijacked by asking questions unnecessary to the objective. I am reminded of findings that unexperienced teachers find spend too much time explaining things. (reference?)
  • Because we didn't meet the data-analysis objective, we didn't try the crux of this lesson, and missed out on many of the measures of innovation. Here is a list of those I think we did manage to cover, noting that I think raters were too generous in rating the presence of "essential features of inquiry."
  1. Instruction is situated in authentic tasks, authentic to the science as scientists do it, if not authentic to the students.
  2. Students and teacher debate ideas and negotiate understanding, hopefully.
  3. The planners are aware of both the degree of guidance and the degree of inquiry, acknowledging that these can be separate.
  4. Students ask (are asked) how well do the data represent the phenomena for which they stand?
  5. Learners pose their own questions. But also
  6. Learners engage in question provided by teacher.
  7. Learner directed toward areas and sources of scientific knowledge.
  8. Learner forms reasonable and logical argument to communicate explanations.
  • I wonder if the freer inquiry is always going to feel less well-managed than the didactic classroom? On the other hand, I have had experiences, though rarely, where students asked the instructor to get out of the way so they could learn better.
References
Brown et al., (Brown, P., Abell, S., & Demir, A. (2006). College science teachers’ views of classroom inquiry. Science Education, 90, (5), 784-802.) on what's missing from science courses.
Measuring Wind Project at EnergyTeachers.org http://energyteachers.org/project_detail.php?project_id=4
WeatherScope, Mesonet, Oklahoma Climatological Survey at http://www.mesonet.org/

Possible pedagogical components for any lesson

See full article on pedagogical components.

From Crawford et al., 2009, page 703
  1. Instruction is situated in authentic tasks;
  2. students develop interdependency in small group work;
  3. students and teacher debate ideas and negotiate understanding;
  4. students and teacher publicly share ideas with members of the classroom community;
  5. students collaborate with experts outside the classroom;
  6. responsibility for learning and teaching is shared.
From Brown et al., 2006, page 799
  1. The planners are aware of both the degree of guidance and the degree of inquiry, acknowledging that these can be separate.
From Schwab, 1962, page 75, these questions posed to the student of enquiry writing a paper
  1. What is the problem under investigation?
  2. From what preceding discoveries and difficulties does it ares?
  3. What data are chosen for search by the scientist?
  4. How well do the data represent the phenomena for which they stand?
  5. What outstanding assumptions are involved in their interpretation?
  6. To what conclusion?
  7. What more is seen when this conclusion is joined to the conclusions of other papers?
From NRC 2000, Inquiry and the National Science Education Standards
Essential Feature Variations, from more learner self-direction to less
1.Learner engages in scientifically oriented questions Learner poses a question Learner selects among questions, poses new questions Learner sharpens or clarifies question provided by teacher, materials, or other source Learner engages in question provided by teacher, materials, or other source
2.Learner gives priority to evidence in responding to questions Learner determines what constitutes evidence and collects it Learner directed to collect certain data Learner given data and asked to analyze Learner given data and told how to analyze
3.Learner formulates explanations from evidence. Learner formulates explanation after summarizing evidence Learner guided in process of formulating explanations from evidence Learner given possible ways to use evidence to formulate explanation Learner provided with evidence
4.Learner connects explanations to scientific knowledge. Learner independently examines other resources and forms the links to explanations Learner directed toward areas and sources of scientific knowledge Learner given possible connections
5.Learner communicates and justifies explanations. Learner forms reasonable and logical argument to communicate explanations Learner coached in development of communication Learner provided broad guidelines to use to sharpen communication Learner given steps and procedures for communication

Todo list

  • Make a clearer histogram, showing units, maybe number of samples.
  • Write a stand-alone program for answering queries of wind data, graphing.