Wednesday, August 27, 2014

RipStik Linear Velocity

The Monday RipStik run exercise ran from the fifth pole at the sidewalk down to the south faculty building entrance. The posts were measured at 305, 305, 305, 307, 307 for a distance sequence of 0, 305, 610, 915, 1222, and 1529. This differs from practice in prior terms where the posts were all taken to be 305 centimeters apart.

Approaching the y-intercept of (0 seconds, 0 centimeters)


Heading downrange, times were 0, 1.22, 2.63, 4.14, 5.55, and 7.25 seconds.

Runs end at the opening to the south faculty building.

Given the weak performance on the pre-assessment, I plant to dissect this data in class on Wednesday. Plot, trend line, slope, and then segment velocity calculations leading into speed changes post-to-post. Slope is speed is the planned theme.

Cleaning the banana patch in ethnobotany class

Just over a year ago the ethnobotany class students planted bananas out in an agricultural area of the college. Each term the students engage in cleaning up the invasive species collection around the bananas, and works on learning some of the varieties of bananas growing in the patch. Although positive identifications will have to await fruiting, the patch is thought to contain karat, menihle (Manila), uhten lihli, uhten ruhk, uhten kapakap, uhten rais, akadahn, kaimana, uhten pisi (Fiji), and daiwang (Taiwan).

Instructor Lee Ling holding Clidemia hirta (riahpen roht), an agressive invasive, and explaining the relationship to the indigenous Melastoma malabathricum var. marianum (pisetikimei).

 Virgina Sartilug works the west edge of the banana patch 

Judy Andon surround by the invasives Costus speciosus (Cheilocostus speciosus) and Clidemia hirta

Katielyne Nianugmwar curring back Clidemia hirta

Ruthy Phillip works while Rockson looks on

Judy sharpens her knife

Joemar Wasan working the east side, the anemic looking banana is under a Spathodea campanulata (African tulip tree), another invasive species.

The instructor enjoying some outdoor activity

Possibly uhten ruhk

Kevina takes a break amid the invasives while Virginia works on

Cleaning towards the southern side

Thursday, August 21, 2014

Ethnobotany day two walk and talk

On the fall schedule this term day two was to be an ethnogarden cleaning exercise. This fall the few plants rescued from the now incomplete soccer field are over behind the gym. On the way across campus I named plants for the class - beginning their preparation for the final examination in December. This slowed progress across campus. On the way across campus I realized that no one had picked up a machete anyway, so I continued the walk and talk tour deviating up to the main road for Magnifera indica and down the LRC for the Ponapea ledermanniana. Around behind the women's residence hall and out into the sea of polystachion grass to learn the few plants that had been moved. Then up into the Japanese "Haruki" cemetery.


Jasmine struggling to survive amidst a sea of polystachion grass.

This walk and talk actually worked rather well as part of the week one introduction to ethnobotany and probably should simply be built upon - using day two not as a garden cleaning day but rather a plant learning day.

Numeric information in graphic forms skills pre-assessment

Underneath the focus on physical systems, SC 130 Physical Science is built on a foundation of connecting physical systems to their mathematical models and communicating the results in writing. Laboratory exercises lead to the writing of a full laboratory report that is marked for content, syntax, grammar, vocabulary, organization, and cohesion.

The majority of the laboratories investigate systems that involve a linear mathematical relationship. Reports include xy scatter graphs, best fit linear trend lines, slope, and y-intercept analysis. The course outline includes the learning outcome, "Students will generate mathematical models for physical science systems." This serves a general education program learning outcome, "Students will be able to present and interpret numeric information in graphic forms," which in turn serves an institutional learning outcome for quantitative reasoning: "Students will be able to reason and solve quantitative problems from a wide array of authentic contexts and everyday life situations; comprehend and can create sophisticated arguments supported by quantitative evidence and can clearly communicate those arguments in a variety of formats."

Twenty-four of the twenty-seven students enrolled in physical science fall 2014 were present the first day. These 24 students completed a pre-assessment consisting of eleven questions which focused on interpreting and generating numeric information in graphic forms.


In general student performance was generally abysmal. The average was 2.60 questions were answered correctly with a median of two questions answered correctly. Twenty-five percent of the class could answer no more than a single question correctly. Bear in mind that many students have completed MS 100 College Algebra, at least three have completed MS 150 Statistics, and two were known to have completed MS 101 Algebra and Trigonometry. One of the MS 101 completers finished MS 101 with a grade of "A."


The question most commonly answered correctly was the plotting of paired xy data presented in tabular format. Nineteen of 24 students successfully plotted the points on a provided graph.

SC 130 Physical Science is designed to address these mathematical weaknesses. The course has as one of its intents the placing of the mathematics into less abstract contexts. The concept is that the laboratory systems and data might provide cognitive hooks on which the students can attach a stronger comprehension of linear mathematical models.

Laboratories one, two, three, four, five, seven, nine, eleven, twelve, and fourteen involve linear relationships between the variables being studied. Non-linear relationships are also generated by some activities in the course. Although the students use spreadsheets to obtain the best fit trend line, the students are still working with concrete systems with variables that are related linearly.

Although fall term 2014 is only just beginning, historically performance improves markedly from the pre-assessment to the post-assessment. Whether students then retain this knowledge through to graduation, or beyond, remains an open question.

Thursday, July 31, 2014

Exploring physical science systems using scientific methodologies

proposed outline for SC 130 Physical Science includes the following three course level student learning outcomes:
  1. Explore physical science systems using scientific methodologies
  2. Generate mathematical models for physical science systems and use appropriate mathematical techniques and concepts to obtain quantitative solutions to problems in physical science.
  3. Demonstrate basic communication skills by working in groups on laboratory experiments and by writing up the result of experiments, including thoughtful discussion and interpretation of data, in a formal format using spreadsheet and word processing software.

The second learning outcome serves, in part, the general education program learning outcome, "3.2 Present and interpret numeric information in graphic forms." Student performance against general education program learning outcome 3.2 was reported on in Numeric information in graphic forms skills pre-post assessment.

The third learning outcome serves, in part, the general education program learning outcome, "1.1 Write a clear, well-organized paper using documentation and quantitative tools when appropriate." Student performance on 1.1 was reported on in Lack of writing improvement in physical science.

The first learning outcome requires that the students be able to explore physical science systems using scientific methodologies. For SC 130 Physical Science this exploration would be framed by the theme of mathematical models that underlie physical science systems. This, in turn, serves the general education program learning outcome, "3.5 Perform experiments that use scientific methods as part of the inquiry process."

The inadequacy of the science curriculum in the elementary and secondary schools does not well prepare students to explore physical science systems in a wholly unguided and unstructured manner. Laboratory fourteen is designed to provide minimal structure and guidance. Laboratory fourteen provides only a system, a suggested starting approach, and an explanation of the equipment being used and the variables being investigated. The system was chosen to be new and unfamiliar to the students.

Emmy Rose, Pamela, and Correy take measurements

In the past the students were provided equipment to investigate whether a mathematical relationship exists between the launch velocity of a flying disk (or ring) and the flight distance. Rain and swampy conditions on the lawn led to a decision to give them a non-linear system - length versus period for a pendulum.

The students were to make a non-statistical determination as to whether a relationship  exists and, if so, whether the relationship is linear. If the relationship appeared to be linear, the students should have known to proceed on to an analysis that included the slope and intercept. A complete laboratory would include a discussion of the sources of error. Although the system is known to be non-linear, at the lengths in use and the errors in measurement made by the teams the system appears to be linear except for the inferred data point at 0 cm length, 0 seconds period.

Eleven of fifteen students completed laboratory report fourteen summer 2014. Note that while students may work in pairs or small groups during the laboratory, each is required to complete their own laboratory report. Four students did not complete the laboratory report. The students had only two school days to complete the report, for some this was insufficient. Earlier laboratories provided one week.



The eleven students who completed the reports all generated data tables with labelled header rows, xy scattergraphs with labelled axes, made a determination of what they thought might be the nature of the mathematical relationship, and generated a trend line equation either linear or non-linear using spreadsheet software.

Seven students decided that the system appeared to be linear, with all seven proceeding to quote the slope and intercept values after determining the system was linear. Note that the order is important: the linear slope and intercept have no meaning unless the system is linear, thus a determination of linearity should precede quoting the slope and intercept. The remaining four students decided the system was non-linear and chose to use quadratic (polynomial) regressions which fit reasonably well to the data. Bear in mind that the students have not been exposed to the theory that drives the pendulum system, nor are they familiar with square root relationships. Over the short lengths investigated a polynomial trend line appears to fit very closely to the data

Two students who chose a non-linear relationship discussed the nature of the relationship in a careful manner than indicated that they understood the system to be non-linear. No report showed evidence that the students had tried to look up the actual relationship. This reflects, in part, the intentional avoidance of refering to using on line resources in the class. In my experience, if the students are told to research a question on line, the students then tend to copy and paste what they find. I prefer to see their own thinking and writing, so I intentionally do not mention using on line resources during the course. This is potentially problematic as the students do not develop a habit of cross-checking results against known on line values or resources. The upside is that I see almost no plagiarism of on line resources in physical science - a common problem I have had in a course such as ethnobotany.

Whether a student should be able to work through a system from raw data to a complete and appropriate mathematical analysis after a single 16 week science with laboratory course is a matter for discussion. At some level all eleven engaged with the data and drew a meaningful, if not fully complete, conclusion.

Laboratory fourteen was designed to provide assessment data pertinent to the first learning outcome on the proposed outline. The other assessments provide information relevant to the other course learning outcomes. By moving to outlines with only course learning outcomes, more insightful assessment is possible. Assessment moves from being static numbers of student success rates, which provide no information on how to improve those numbers, to real insights into what the students know, what the students can do, and what the students value.

Wednesday, July 30, 2014

Lack of writing improvement in physical science for summer 2014

proposed outline for SC 130 Physical Science includes the following three course level student learning outcomes:
  1. Explore physical science systems using scientific methodologies
  2. Generate mathematical models for physical science systems and use appropriate mathematical techniques and concepts to obtain quantitative solutions to problems in physical science.
  3. Demonstrate basic communication skills by working in groups on laboratory experiments and by writing up the result of experiments, including thoughtful discussion and interpretation of data, in a formal format using spreadsheet and word processing software.
The third learning outcome serves, in part, the general education program learning outcome 1.1, "Write a clear, well-organized paper using documentation and quantitative tools when appropriate." This article notes the lack of improvement in writing skills during the summer term as measured by a rubric, a reverse of the finding during the regular term.

When I took over and redesigned SC 130 Physical Science in 2007 I had two focuses. The dual focuses were to put mathematics and writing into the core of the course. By building laboratories around mathematical models and having students write up the results of those laboratories in reports marked for content, grammar, vocabulary, organization, and cohesion, both goals were simultaneously achieved. A previous report looked at improvement in mathematical graphical analysis skills, this report looks at the improvement in writing. A third report looks at the first course level student learning outcome.

The redesigned course is intended to include support for the general education program student learning outcome 1.1, "Write a clear, well-organized paper using documentation and quantitative tools when appropriate." The course also now serves the second institutional learning outcome, "Effective written communication: development and expression of ideas in writing through work in many genres and styles, utilizing different writing technologies, and mixing texts, data, and images through iterative experiences across the curriculum." The laboratory reports include tables and charts prepared in a spreadsheet and then inserted into the final report using word processing software. Effective written communication also requires command and control of grammar, vocabulary, organization, and cohesion. This article reports on these writing metrics in a non-language and literature course.

The course includes 15 laboratories. Odd numbered laboratories include a full write-up with grammar, vocabulary, organization, and cohesion being marked. The exception is that laboratory 15 is not turned-in, so laboratory 14 is done as a full write-up laboratory. In the regular term eight full laboratory reports are done during 16 weeks. In the shorter summer term six full laboratory reports are done in six weeks. Either the reduction in the number of laboratories, the shorter term, relatively high scores on the pre-assessment, or other factors unique to the class led to no improvement in writing schools as measured by a rubric used in the course.

Grammar (G), vocabulary (V), organization (O), and cohesion (C) are scored using a rubric with a total possible of 20 points. Each of the four metrics are scored on a 0 to 5 point scale. The rubric was reported in an earlier blog article. Laboratories one (1) and fourteen (2 in the chart) were analyzed.


No improvement was seen on any of the four metrics. The difference in the averages was not significant for any metric. The change in each was no different from zero. Part of the reason for this may have been relatively strong writing performance on the first laboratory and relatively weaker or unimproved writing on the fourteenth laboratory. The nature of the short summer term and the fewer number of full write-up laboratories likely also contributed to performance being unchanged.

Improving writing during the short time available in the summer term may not be possible in a course such as physical science where writing is not the primary learning outcome but only one of three outcomes.

In a separate note, a proposal to put only course level student learning outcomes on outlines at the college is an excellent concept. The reduction from the number of specific student learning outcomes is exactly what allows for an analysis such as the one above - an analysis that I believe generates real and actionable information on learning. In the earlier report on mathematical models and techniques an improvement was noted, learning was documented. In this report improvement was not shown, raising questions about whether a  writing across the curriculum approach will have impact in summer courses. These questions can then be explored in future summer terms. Course outlines should move to including only course level student learning outcomes, permitting instructors to provide more thoughtful analysis of those outcomes.

Saturday, July 26, 2014

Liked and disliked laboratories

Laboratories are at the core of the SC 130 Physical Science. While in-class tests and quizzes provide information on academic achievement, how the students react affectively to these laboratories is also important in the course design.


Pamela Edgar tests unknowns to determine if they are an acid or base.

The course is not listed as a requirement by any major at the college, thus the course most frequently serves students taking the course to satisfy their general education science with laboratory requirement. The students are not planning a career in science and likely contain a larger percentage of students for whom science is not attractive as a subject of study. A goal of mine is to open up the thinking of the students. My best hope is that through the course the students will come to have an interest in science, see that even simple topics can be interesting, and gain an appreciation of how science is done.

As an affective learning domain study, students were asked to choose their favorite laboratory and provide comments on why that laboratory was their favorite. The students were also asked to choose their least favorite laboratory and explain why they disliked that laboratory.

The laboratories this past term were:

1. Laboratory one: Density of soap
2. Laboratory two: Velocity of a rolling ball
3. Laboratory three: Acceleration of gravity by dropping a ball
4. Laboratory four: Momentum of marbles colliding on a table (on a poster sheet on the table, no track used. Issues of aim and off-center hits proved problematic)
5. Laboratory five: Force, pulleys, mechanical advantage
6. Laboratory six: Increase in length of a pipe due to heat (although considered a failure by me, two students would report liking this laboratory.
7. Laboratory seven: Using a GPS to calculate meters per minute of latitude
8. Laboratory eight: Cloud drawings
9. Laboratory nine: Sound:, clapping wood blocks to determine the speed of sound
10. Laboratory ten: Spectra, RGB colors, hue saturation luminosity, HTML (Computer lab was free this term at lab time)
11. Laboratory eleven: Reflection in a mirror and apparent depth of pennies underwater
12. Laboratory twelve: Batteries and bulbs, conductors, Ohm's law
13. Laboratory thirteen: Chemistry, acid and base detection using flowers
14. Laboratory fourteen: The search for the mathematical relationships between length and period for a pendulum (due to rain the flying disk variation was not deployed).
15. Laboratory fifteen: Site swap notation and juggling.

The terms are coded in the data table further below in the following manner.

93: Fall 2009
a1: Spring 2010
a2: Summer 2010
a3: Fall 2010
b1: Spring 2011
c1: Spring 2012
d1: Spring 2013
e1: Spring 2014
e2: Summer 2014

 The survey results were compiled and are reported below. The laboratories are listed on the left side, the terms across the second row. All net is the sum of the like votes minus the sum of the dislike votes. The second to last column, e2 net, is the spring 2014 likes minus the dislikes, the last column, rng (range), is the sum of the likes and dislikes. The larger the range, the greater the dichotomous spit in the voting.


Like Dislike all e2
Lab 93 a1 a2 a3 b1 c1 c2 d1 d3 e1 e2 93 a1 a2 a3 b1 c1 c2 d1 d3 e1 e2 net rng net rng
1 1 2
1 2 2 1 4 3
3 1
2 1 2
2
1

10 28 3 3
2 1
1
1 2


2


2
1 1


1
2 12 0 0
3
2

1





1 1
1
2
1

1 -4 10 -1 1
4


1 1 1





1
3 3 4 1



-9 15 0 0
5
1






1
1
1 2 1

1


-4 8 0 0
6 1
2






2




2
1 1 2
-1 11 2 2
7 11 6 3 7 1 4 7 7 4 3 2 9 8 2 6 2 2 2 1
4 2 17 93 0 4
8 6 4 7 8 8 3
5
7 3 6 7 4 1 7 3 9 9 5 4 3 -7 109 0 6
9

2
2 5 2
2 1 1 4 2 7 5 6 2 1 2 1 2 2 -19 49 -1 3
10 7 3
5 7 2
3 1 1
1 2 2 2 4 2
1 2

13 45 0 0
11
3
2
2


1
1 1 1 4


1

1 -1 17 -1 1
12 2 3 2 2
1 2
1 4
5 1 4 5 3 3
3 2 2
-11 45 0 0
13 1 10 10 6 12 7 3 7 6 3 1 4 3
1 2 3
4 2 3
44 88 1 1
14







2 1








2 2 1 -2 8 -1 1
15








2 1







1 1 3 -2 8 -2 4

One and eight were the most favored laboratory with three votes each. On aggregate laboratory thirteen remains the most favored with a net of 44 more likes than dislikes.

Eight and fifteen received the strongest negative ratings with fourstudents each listing these as their most disliked laboratories. Laboratory eight was both liked and disliked. Laboratory eight almost always evokes this dichotomous reaction in students.

Note that some students simply say that they liked all labs, or disliked none, thus totals do not add to the sample size.

In the affective domain, the proof is in the details and the individual comments by students provide this insight.

Liked laboratory comments:
1 I enjoyed it. It was fun.
1 Everything
1 I get to understand more about the density of soap. I never thought that the reason soap sinks is due to its density being more than one and when they float, their density is less than one.
6 Interesting because I did not think it was possible
6 No reason
7 This lab was fun. finding Binky was exciting.
7 Gave us knowledge on how to use GPS.
7 I learn how to actually use a GPS to find something
8  I feel free and draw what and which drawing to make.
8 I like to draw things that interested to people
8 I know some other clouds name
9 Only few participate in this laboratory
13 It does not involve math equation and graph. All the things we used in this lab are available here in Pohnpei and we can use this laboratory in our elementary classroom
15 It was fun. Taught me how to use three balls.

Dislike laboratory comments:
3 I did not do well in this laboratory
7 I did not know how to use the GPS.
7 I got none of it correct
8 I am not good at drawing.
8 I do not know how to draw anything, I hate this lab, even though it was the easiest lab out of all the labs.
8 I hate drawing
9 I did not get points for that lab because did not join the teacher do the lab because it was raining.
9 I didn't get any points from this lab
9 I missed what we have done and don't know we will go to other places to do the work
11 I don't really understand the field
14 I did not quite understand the mathematical relationships before taking this laboratory
15 I really got confused with all the numbers where the ball land.
15 I didn't get to understand more about it especially the site swap notation, not the juggling.
15 I was not very good at it

Comments that note a laboratory was interesting or fun directly support my own goals in the course. Once something is interesting and fun, the student becomes a self-driven learner. And learning only really occurs when a person wants to learn. If I can generate the desire, then the learning can follow.