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32 nd International Conference on Technology in Collegiate Mathematics VIRTUAL CONFERENCE ictcm.com | #ICTCM 32 nd International Conference on Technology in Collegiate Mathematics VIRTUAL CONFERENCE #ICTCM How Learning Catalytics Changed


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32nd International Conference on Technology in Collegiate Mathematics

ictcm.com | #ICTCM

VIRTUAL CONFERENCE

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32nd International Conference on Technology in Collegiate Mathematics VIRTUAL CONFERENCE

#ICTCM

“How Learning Catalytics Changed My Mind About Using Smart Devices in the Classroom” Heather Manhart; Instructor Department of Mathematics Campbell University

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32nd International Conference on Technology in Collegiate Mathematics VIRTUAL CONFERENCE

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Abstract

  • Once an adversary to the use of smart devices in the

classroom, I never thought that the Learning Catalytics

  • ffered through Pearson’s MyStatLab could enhance

my lectures.

  • After

successfully delivering a Learning Catalytic assessment to my students, I found that reviewing the question and showing how to come up with the answer correctly, helped my students to assess themselves, which in turn, allowed them to ask me more questions to clear up any misunderstandings of the topic at hand.

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32nd International Conference on Technology in Collegiate Mathematics VIRTUAL CONFERENCE

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Abstract (Continued)

  • Through trial and error, I soon realized how user friendly Pearson made

Learning Catalytics. I began forming questions that were multiple-choice, short answer, and word clouds by nature. I learned how each type of question benefited my students in different ways; all of which quickly assessed my students’ knowledge of the many topics presented in a statistics course.

  • As for using smart devices to submit answers to the Learning Catalytics given

in the classroom, I devised a “Smart Device Usage Policy” for my students with clear guidelines. I reduced the amount of smart device usage for unauthorized purposes by clearly stating the consequences and by standing firm behind the penalties.

  • My hope for this presentation of how Learning Catalytics enhance student

engagement is that participants will reconsider allowing Smart Devices during their lectures, if only for the purpose of student assessment. Needless to say, I am now an advocate for using smart devices in the classroom.

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32nd International Conference on Technology in Collegiate Mathematics VIRTUAL CONFERENCE

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So Why Use Learning Catalytics in the Classroom?

  • Learning Catalytics give the instructor a way to quiz 40 or

more students easily.

  • The grades for Learning Catalytics automatically synchronize

to the Blackboard Grade Book.

  • Learning Catalytics make class lectures more interesting and

keep students engaged.

  • Learning Catalytics help students achieve higher end-of-

course grades.

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Large Classes ~ 40 or More Students (My Summer 2019/Fall 2019/Spring 2020 Class Schedule)

Semester Course and Section Course Name Number of Students Credit Hours Summer I 2019 MATH 160 – 1 Elementary Statistics 13 Students 3 credits MATH 122 – 1 Calculus I 13 Students 4 credits Fall 2019 MATH 160 – 1 Elementary Statistics 49 Students 3 credits MATH 160 – 5 Elementary Statistics 47 Students 3 credits MATH 223 – 1 Calculus II 28 Students 4 credits MATH 223 – 2 Calculus II 15 Students 4 credits Spring 2020 MATH 160 – 1 Elementary Statistics 40 Students 3 credits MATH 160 – 4 Elementary Statistics 43 Students 3 credits MATH 160 – 7 Elementary Statistics 43 Students 3 credits MATH 223 – 1 Calculus II 17 Students 4 credits

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Learning Catalytics Synchronize to the Blackboard Grade Book

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Example One: How Learning Catalytics Keep Students Engaged in Lecture ~ Multiple-Choice Question

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32nd International Conference on Technology in Collegiate Mathematics VIRTUAL CONFERENCE

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Example Two: How Learning Catalytics Keep Students Engaged in Lecture ~ Word Cloud Question

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Learning Catalytics Improve the Students’ End-of-Course Grades

How?

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Grades for Spring Semester 2020

  • Course: MAT 160 Elementary Statistics
  • Number of Sections for Course: 3
  • Total Number of Students: n = 126
  • Students Divided Into Data Sets A and B
  • Data Set A: Grades Prior to Coronavirus Pandemic

(Classes were seated and LC Quizzes Given.)

  • Data Set B: Grades Post-Coronavirus Pandemic

(Classes were online and LC Quizzes Not Given. Other Types of Quizzes Were Given.)

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Tests, Quizzes, and MyStatLab Assignments

Pre-Coronavirus (6 LC Quizzes Given)

Tests and Assignments MAT 160_Section 1 Spring 2020 Test One: Chapters 1 and 2 Test Date: Thursday, February 6th Definitions and Measuring Data MSL Homework: Averages MSL Homework: Variation MSL Homework: Position Chapters One and Two Due Thursday, Feb. 6th at 8:00 a.m. (submit online) Test Two: Chapter 5 Test Date: Thursday, February 27th The Normal Distribution MSL Homework: Standard Normal MSL Homework: Normal Distrib. Prob. MSL Homework: Normal Distrib. Cut-Offs MSL Homework: Sampling Distrib. Chapter Five Due Thursday, February 27th at 8:00 a.m. (submit online)

Post-Coronavirus (8 Non-LC Quizzes Given)

Test Three: Chapter 6 Test Date: Thursday, March 26th Confidence Intervals MSL Homework: Z-Intervals MSL Homework: T-Intervals MSL Homework: Proportion Intervals MSL Homework: Chi-square Intervals Chapter Six Due Thursday, March 26th 8:00 a.m. (submit online) Test Four: Chapter 7 Test Date: (See Final Exam Schedule.) Hypothesis Testing MSL Homework: Z-Tests MSL Homework: T-Tests MSL Homework: Proportion Tests MSL Homework: Chi-square Tests Chapter Seven Due Reading Day: Thursday, April 23rd at 8:00 a.m. (submit

  • nline)
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Two Sets of Data

  • Set A: Pre-Coronavirus Pandemic Final Grade

50% Test Average (Test 1 and Test 2) 25% Quiz Average (LC Quizzes Only) 25% MyStatLab Assignment Average (Assignments Completed Pre-Coronavirus)

  • Set B: Post-Coronavirus Pandemic Final Grade

50% Test Average (Test 3 and Test 4) 25% Quiz Average (LC Quizzes Not Given/Other Online Quizzes Given) 25% MyStatLab Assignment Average (Assignments Completed Post-Coronavirus)

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How Did Grades Compare Pre-Coronavirus to Post-Coronavirus?

  • Final Grade for Set A > Final Grade for Set B
  • Quiz Average for Set A > Quiz Average for Set B
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Excel Spreadsheet ~ Page One

Set A Set B Set A Set B

Pre_Coronavirus Post_Coronavirus Pre_Coronavirus Post_Coronavirus First Name

Final Grade LC’s Only Final Grade Non-LC’s/Other Quiz Average LC’s Only Quiz Average Non-LC’s/Other

  • 1. Brian

95.875 97.21875 100 93.875

  • 2. Georgeanna

94.87904 94.75 83.33333 100

  • 3. Lydia

84.29166 83.62062 66.66666 91.875

  • 4. Ashley

87.54166 98.04562 66.66666 100

  • 5. Marqueese

47.0119 24.85625 33.33333 12.5

  • 6. Jensen

84.70833 59.92156 83.33333 57.5

  • 7. Alexis

89.82761 71.755 83.33333 44.75

  • 8. Meredith

91.70833 85.62343 83.33333 86.5

  • 9. Keegan

84.49404 81.00781 83.33333 72.5

  • 10. Sophie

94.81547 85.98531 83.33333 83

  • 11. Magic

82.28988 76.99968 66.66666 58.5

  • 12. Camryn

100.75 100 100 100

  • 13. Shaleah

94.25 91.085 100 98.875

  • 14. Breanna

61.53571 68.82 50 62.75

  • 15. Houston

94.95833 88.10968 83.33333 77

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Excel Spreadsheet ~ Page Two

  • 16. Jackson

97.5 86.0675 100 74

  • 17. Megan

85.69452 79.68625 66.66666 85

  • 18. Gustavs

80.33333 93.5425 83.33333 86.5

  • 19. Joshua

76.12309 73.74125 66.66666 74

  • 20. Richard

70.375 79.89312 50 74.125

  • 21. Joshua

94.25 91.23625 100 93.875

  • 22. Essence

88.14869 85.5325 83.33333 53.375

  • 23. Kaitlin

99.125 96.25 100 100

  • 24. Joseph

90.08333 74.56906 83.33333 43.125

  • 25. Kasey

84.07726 90.93812 83.33333 88.375

  • 26. Tamara

85.91666 78.98562 66.66666 56.375

  • 27. Dervon

89.81261 87.48593 83.33333 85

  • 28. Faith

62.25 93.425 50 87.5

  • 29. Ethan

92.08333 75.665 83.33333 87.5

  • 30. Kathleen

93.33333 98 83.33333 100

  • 31. Fredrick

94.95833 92.21875 83.33333 70.875

  • 32. Sharice

71.67773 70.32937 66.66666 42.625

  • 33. MacKenzie

87.27095 86.95187 66.66666 85.5

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Excel Spreadsheet ~ Page Three

  • 34. Brittany

88.25 95.3375 50 97.75

  • 35. Naelee

78.79297 80.41437 83.33333 69.375

  • 36. Rebekah

94.95833 97.97843 83.33333 100

  • 37. Kirkland

88.45833 94.9175 83.33333 100

  • 38. Devin

87.54166 40.46375 66.66666 40

  • 39. John

86.15476 85.90562 83.33333 84.5

  • 40. Brittney

97.26178 97.22468 100 100

  • 41. John

70.29749 90.73 57.14285 88.25

  • 42. Amaria

67.87499 74.01875 42.85714 66.5

  • 43. Reggie

69.07142 64.925 71.42857 54.75

  • 44. Lakelyn

97.5 98.25 100 99

  • 45. Dustin

82.34321 76.60125 57.14285 64.125

  • 46. Joseph

61.67857 82.29156 57.14285 64.125

  • 47. James

81.64285 73.71 100 51.875

  • 48. Dailyn

78.15749 85.59718 71.42857 87.5

  • 49. Grace

71.60107 88.92625 42.85714 94

  • 50. Allison

80.60714 89.34437 71.42857 96.75

  • 51. Mikaylee

87.75 93.93312 100 100

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Excel Spreadsheet ~ Page Four

  • 52. Ashley

97.5 89.26125 100 71.375

  • 53. Sarah

79.01785 93.48562 71.42857 100

  • 54. Joy

81.16071 88.875 71.42857 82.5

  • 55. Melissa

90.79571 87.05406 85.71428 82

  • 56. Cameron

98.76785 96.16062 100 85

  • 57. Jesse

99.125 90.26343 100 85.5

  • 58. Cedric

46.64285 74.97156 42.85714 42.5

  • 59. Jackson

76.51785 72.59343 71.42857 64.875

  • 60. Gabriel

92.30357 67.45343 85.71428 54.875

  • 61. Margaret

97.5 92.30125 100 93.875

  • 62. Alex

71.56964 67.05562 100 35.375

  • 63. Carson

97.5 98 100 100

  • 64. Zachary

74.64392 61.79875 57.14285 44.125

  • 65. Payal

83.38107 82.91781 71.42857 68.375

  • 66. Michael

82.23214 80.07156 71.42857 80.5

  • 67. Yasantaia

82.07357 76.40531 71.42857 78.625

  • 68. Sarah

78.18857 72.07625 71.42857 51

  • 69. Svenia

93.92857 93.75 85.71428 95

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Excel Spreadsheet ~ Page Five

  • 70. Claudiu

74.76785 60.32718 85.71428 61

  • 71. Jason

65.85714 65.2675 71.42857 59.625

  • 72. Kiara

85.32749 71.70968 85.71428 55.375

  • 73. Isabella

100.75 81.7175 100 50

  • 74. Samantha

80.92857 86.44812 85.71428 100

  • 75. Justin

94.66071 94.05 85.71428 95

  • 76. Lauren

85.48214 97.2175 71.42857 100

  • 77. McKenna

86.53571 81.2525 85.71428 70

  • 78. Sol

69.47428 78.31125 85.71428 75

  • 79. Chandler

85.80357 80.62 85.71428 70.75

  • 80. Ashley-Joyce

95.875 56.57656 100 25

  • 81. Samuel

77.60714 73.73343 57.14285 81.5

  • 82. Kendall

88.97428 88.40281 85.71428 94.375

  • 83. Nancy

93.92857 94.425 85.71428 97.5

  • 84. Cameron

95.875 87.76125 100 85.375

  • 85. Emma

70.54857 57.89812 50

  • 86. O'Neshia

75.67261 40.88125 83.33333 19.25

  • 87. Barbara

100.75 82.69875 100 70.375

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Excel Spreadsheet ~ Page Six

  • 88. Hannah

77.13821 75.55375 50 77

  • 89. Robert

100.75 97.25 100 99

  • 90. Stephanie

94.25 88.5 100 83

  • 91. Helen

88.86916 83.27875 66.66666 73

  • 92. Andrew

94.95833 96.34375 83.33333 94.375

  • 93. Ricky

51.07226 83.58812 33.33333 72.875

  • 94. Aliyah

93.33333 95.8 83.33333 99

  • 95. Madison

86.26785 95.91375 50 100

  • 96. Timon

76.875 88.16375 50 90.625

  • 97. Taye

94.25 87.25156 100 87.5

  • 98. Elana

99.125 96.57625 100 100

  • 99. Thomas

89.16666 83.19 66.66666 86.125

  • 100. Maddie

94.95833 97.465 83.33333 95.25

  • 101. Tamera

99.125 92.875 100 97.5

  • 102. Quincy

77.18773 88.30812 66.66666 100

  • 103. Jack

74.3988 73.30968 66.66666 56.25

  • 104. Dakota

92.30357 93.375 100 82.5

  • 105. Michael

51.31047 59.61562 33.33333 23.25

  • 106. Brianna

89.78976 92.21062 83.33333 93.75

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Excel Spreadsheet ~ Page Seven

  • 107. Ronald

72.79369 54.88031 83.33333 47.5

  • 108. Janely

78.70833 89.99625 83.33333 84.375

  • 109. Ian

95.16071 98.3325 100 100

  • 110. Melody

66.9069 61.29875 83.33333 29.375

  • 111. Nicholas

84.8869 58.595 83.33333 44.25

  • 112. MacKenzie

71.77678 84.97625 50 87.5

  • 113. Hannah

81.75 93.48625 50 96.875

  • 114. Kayleigh

67.09821 88.8525 50 85.875

  • 115. Elizabeth

97.5 87.80687 100 86.375

  • 116. Samuel

88.5119 64.5375 83.33333 61.5

  • 117. Allison

96.58333 99.0825 83.33333 99

  • 118. Donavon

89.36321 63.96406 100 72.625

  • 119. Erik

80.5594 65.44687 83.33333 25

  • 120. Emilie

82.86904 87.85281 83.33333 99

  • 121. Gabriel

69.60142 88.4175 50 100

  • 122. Olivia

68.7419 38.425 33.33333 37.5

  • 123. Hannah

91.70833 83.6425 83.33333 97.5

  • 124. Andrea

97.05357 92.5425 100 98

  • 125. Samantha

88.45833 100 83.33333 100

  • 126. Michael

99.125 89.30468 100 85

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Excel Spreadsheet Results

n = 126 Students Total Set A Set B Set A Set B

Pre_Coronavirus Post_Coronavirus Pre_Coronavirus Post_Coronavirus

Final Grade LC’s Only Final Grade Non-LC’s/Other Quiz Average LC’s Only Quiz Average Non-LC’s/Other Sample Means 84.506715 82.35467302 78.04232532 76.66468254 Sample Std. Dev. 11.90398394 14.18088498 18.36117657 22.83256255 Coefficient of Variation 14.08643554 17.21928393 23.52720334 29.78237409 ≈ 14% ≈ 17% ≈ 24% ≈ 30% Less Varied More Varied Less Varied More Varied More Consistent Less Consistent More Consistent Less Consistent

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Box & Whisker Plot (Final Grades)

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Box & Whisker Plot (Quiz Averages)

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Summary

  • In the end, the Final Grades and Quiz Averages for Pre-Coronavirus

compared to Post-Coronavirus were higher, even if not by very much. However, remember that receiving higher grades was only one of the “4” reasons why I use Learning Catalytics in the classroom.

  • As for allowing Smart Devices in the classroom for the purpose of

administering Learning Catalytics to my students, the many advantages

  • f using Learning Catalytics in the classroom far out-weighed any

negative associations with students using their smart devices during my

  • lectures. I devised a “smart device” usage policy for my courses and my

students to adhere to within the classroom setting. By outlining a strict policy for my students with clear guidelines, I reduced the amount of smart device usage for unauthorized purposes.

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Contact Information

  • Name: Heather Manhart
  • Title: Instructor of Mathematics
  • Institution: Campbell University
  • Email: manharth@campbell.edu

Thank you for viewing my presentation.