Fun Literature References & Lesson Guidance

References

OVERALL 

ART GALLERY

  • Lipovetsky, S., & Mandel, I. (2009). How art helps to understand statistics. Model Assisted Statistics and Applications, 4(4), 313-324.

CARTOONS

  • Lesser, L. (2018). Classroom notes: 'One in ten'. Teaching Statistics, 40(1), 33-34.
  • Özdoğru, A. A., & McMorris, R. F. (2013). Humorous cartoons in college textbooks: Student perceptions and learning. Humor, 26(1), 135-154. 
  • Schacht, S. P., & Stewart, B. J. (1990). What’s so funny about statistics? A technique for reducing student anxiety. Teaching Sociology, 18(1), 52-56. 

GAMES/PUZZLES

  • Kuiper, S., & Sturdivant, R. (2014). Games as a locus of self-empowered collaborative learning. In K. Makar, B. de Sousa, & R. Gould (Eds.), Sustainability in statistics education. Proceedings of the Ninth International Conference on Teaching Statistics (ICOTS9, July, 2014), Flagstaff, Arizona, USA. Voorburg, The Netherlands: International Statistical Institute.  http://icots.info/9/proceedings/pdfs/ICOTS9_C117_KUIPER.pdf
  • Kuiper, S., & Sturdivant, R. X. (2015). Using online game-based simulations to strengthen students' understanding of practical statistical issues in real-world data analysis. The American Statistician, 69(4), 354-361.

  • Lesser, L. (2022). Culturally responsive teaching of probability: [the games of] Toma Todo and La Loteria.
    https://www.causeweb.org/cause/ecots/ecots22/program/activity-contest/2

JOKES/HUMOR

  • Berk, R. A., & Nanda, J. P. (1998). Effects of jocular instructional methods on attitudes, anxiety, and achievement in statistics courses. HUMOR: International Journal of Humor Research, 11(4), 383–409. 
  • Friedman. H. H., Friedman, L. W., & Amoo, T. (2002). Using humor in the introductory statistics course. Journal of Statistics Education, 10(3), http://www.amstat.org/publications/jse/v10n3/friedman.html.
  • Lomax, R. G., & Moosavi, S. A. (2002). Using humor to teach statistics: Must they be orthogonal? Understanding Statistics, 1(2), 113-130.
  • Neumann, D.L., Hood, M. and Neumann, M.M. (2009). Statistics? You must be joking: The application and evaluation of humor when teaching statistics. Journal of Statistics Education, 17(2), https://www.tandfonline.com/doi/pdf/10.1080/10691898.2009.11889525. 

KINESTHETIC

MAGIC

  • Lesser, L. M., & Glickman, M. E. (2009). Using magic in the teaching of probability and statistics. Model Assisted Statistics and Applications, 4(4), 265-274.
  • Wiseman, R. & Watt, C. (2020). Conjuring cognition: a review of eductional magic-based interventions. PeerJ: The Journal of Life and Environmental Sciences, http://doi.org/10.7717/peerj.8747​  https://peerj.com/articles/8747/​.

POEMS

  • Connor-Greene, P. A., Young, A., Paul, C. P., & Murdoch, J. W. (2005). Poetry: It’s not just for English class anymore. Teaching of Psychology, 32(4), 215-221.​
  • Keller, R., & Davidson. D. (2001). The math poem: Incorporating mathematical terms in poetry, Mathematics Teacher, 94(5), 342-347.
  • LaBonty, J., & Danielson, K. E. (2005). Writing poems to gain deeper meaning in science, Middle School Journal, 36(5), 30-36.
  • Lesser, L. (2021), R is for Rhyme? Statistics Class 'Stanza Part' with Poetry!, Proceedings of the 2021 Joint Statistical Meetings [View]

QUOTES

  • Gaither, C. C., & Cavazos-Gaither, A. E. (1996), Statistically speaking: A dictionary of quotations. Boca Raton, FL: CRC Press. 

SHORT STORIES

  • Young,T.A., McDuffie,A.R., & Ward, B.A. (2018). Selecting a good book for mathematics instruction, in Monroe, E.E. et al. (Eds.), Deepening Students' Mathematical Understanding with Children's Literature (pp. 39-60), Reston, VA: NCTM.

SONGS

VIDEOS

  • Petty, N. W. (2014). Taking statistical literacy to the masses with YouTube, blogging, Facebook and Twitter. In K. Makar, B. de Sousa, & R. Gould (Eds.), Sustainability in statistics education. Proceedings of the Ninth International Conference on Teaching Statistics (ICOTS9, July, 2014), Flagstaff, Arizona, USA. Voorburg, The Netherlands: International Statistical Institute. http://iase-web.org/icots/9/proceedings/pdfs/ICOTS9_7A3_PETTY.pdf
  • Berk, R. A. (2009). Multimedia teaching with video clips: TV, movies, YouTube, and mtvU in the college classroom. International Journal of Technology in Teaching and Learning, 5(1), 1–21. http://www.ronberk.com/articles/2009_video.pdf 

Lesson Guidance

The bibliography above is intended to give representative points of departure of papers that explore a particular modality in the specific context of teaching or learning statistics. Suggestions of more recent, comprehensive, or useful references are always welcome. Also, see how multiple types of fun are incorporated and integrated for a particular topic in each installment of the "Statistical Edutainment" column in Teaching Statistics (Fall 2019 – present).

While every modality and teaching context will have its own nuances, there are some general principles that may apply to the large majority of planned usages. To this end, we have compiled a list (adapted from the guiding questions in the 2008 Lesser & Pearl JSE paper) that can serve as a template for teachers:

EXAMPLE 1:

Description (From the full CAUSEweb record description at: https://www.causeweb.org/cwis/r1248/song_what_p-value_means): Song is simply a quick jingle to help students recall the conceptual interpretation of a p-value. May be sung to tune of "Row, Row, Row Your Boat". Recorded June 26, 2009 at the OSU Whisper Room: Larry Lesser, vocals/guitar; Justin Slauson, engineer.

URL for lyric and soundfile: http://www.causeweb.org/resources/fun/db.php?id=86

Length of song: 10 seconds

Goal: helping students learn (and practice saying) the interpretation of a p-value

Target audience: students in any class that introduces p-values

Set-up: discuss a real-life vignette's probability such as "in a 10-child family, 9 babies were girls". Discuss what would be even more "extreme" (10 of 10 girls; if two-tailed, 9 or 10 boys as well) and unpack that there is an implicit null hypothesis that the probability of a birth being a girl is about 0.50, and that the 7 of 7 feels unusual because under the null hypothesis of independent births with P(girl) = 0.5 each time, it seems very unlikely to get 9 or more of the babies to be girls. Play the song.

In-class Use: Play the soundfile (http://www.causeweb.org/resources/fun/db.php?id=86) so students can hear the song (and read the lyric at the same time, making sure you select an updated browser that allows this).  Then play it again and have the class sing along. For more adventurous classes, try singing it in a two-part round as "Row, Row, Row Your Boat" would be (i.e. after one half of the room finishes "It is key to know," the other half begins the song as done in the video at www.youtube.com/watch?v=CJrXuooX7hI.

Online self-paced use: instruct students to do a “set-up” reading, then click on the soundfile to play the song several times, then click on the “follow-up” reading. Alternatively, instructors can have students go to https://www.causeweb.org/smiles/songs/what_p-value_means  and answer the three questions before having the song revealed.

Follow-up: recap the pieces of the song to make sure students understand what is meant by "extreme" (try a different scenario to assess this and move away from the p=0.5 null hypothesis: a basketball player makes 7 of 10 free throws) and give examples that are one-tailed and examples that are two-tailed. Emphasize the conditional (i.e., “if the null hypothesis is true, then the probability of….”) structure of the interpretation of a p-value.

Assessment: on the next midterm or quiz, try a relevant CAOS-pool item from the ARTIST database (https://apps3.cehd.umn.edu/artist/ or https://apps3.cehd.umn.edu/artist/tests/index.html); or here’s a multiple-choice item adapted from Vogt, 2007 p. 13:

A p-value of .03 means:

  1. There’s a 3% chance the null hypothesis is wrong.
  2. The probability that the result is due to chance (is a coincidence) is 3%.
  3. A result of this size would occur by chance alone 3% of the time.
  4. If the null hypothesis were true, the probability of getting a result at least this far away from the null hypothesis would be 3%.

EXAMPLE 2:

From the full CAUSEweb record description at: https://www.causeweb.org/cwis/r1819/cartoon_the_beanstalks

Description: A cartoon to teach the idea that the mean is affected by outliers while the median is not. Cartoon by John Landers (www.landers.co.uk) based on an idea from Dennis Pearl (then at Ohio State University). Free to use in the classroom and on course web sites.

URL for cartoon: https://www.causeweb.org/cause/resources/fun/cartoons/beanstalks?id=258

Goal: helping students review the interpretation of mean and median and the affect of outliers on them (material that would have been first taught in middle school or high school)

Target Audience: students in introductory courses

Set-up: Ask for a show of hands or use as a clicker question: “Did you smoke any cigarettes yesterday? (yes/no)”  Then ask “What is the median number of cigarettes students in this class smoked yesterday?” (since almost assuredly a majority of students in your class will not have smoked any cigarettes,  the answer to this will be zero).  Then ask: “Would the mean number of cigarettes smoked also be zero or would it be bigger?” (since almost assuredly there will be at least one smoker in the class, the answer to this questions would be bigger than zero).

Show the cartoon.

Follow-up:  In class discussion question: Why would Jack be more interested in bragging about the mean height of the beanstalks?

Clicker Assessment:

  • Which measure - mean or median - would be better to use if you wanted to describe the typical size of a beanstalk in the cartoon?
  • Which measure would be better to use if you wanted to describe the total size of the whole bean crop?