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Table 7 Mixed-effects logistic regression model used to predict use of lateral reading and correct trustworthiness conclusion on each problem (N = 230)

From: Improving college students’ fact-checking strategies through lateral reading instruction in a general education civics course

Predictor variables

B (SE)

Odds ratio (95% CI)

z

X2

Intercept

− 8.62 (1.19)

0.00 (0.00, 0.00)

− 7.24***

Media literacy accuracy at pretest

1.07 (0.80)

2.92 (0.61, 14.09)

1.33

1.83

Lateral reading at pretest (No = 0)

1.22 (0.61)

3.39 (1.02, 11.24)

1.99*

4.07*

Instructor (Instructor 1 = 0)a

10.50*

 Instructor 2

0.68 (0.51)

1.98 (0.73, 5.37)

1.33

 Instructor 3

0.22 (0.48)

1.25 (0.49, 3.18)

0.47

 Instructor 4

1.41 (0.51)

4.10 (1.52, 11.08)

2.78**

Problem type (sourcing evidence = 0)a

35.60***

 Clickbait science and medical disinformation

0.79 (0.38)

2.19 (1.03, 4.65)

2.05*

 Fake news

2.00 (0.39)

7.40 (3.47, 15.77)

5.19***

 Photographic evidence

1.13 (0.38)

3.09 (1.47, 6.50)

2.97**

Condition (Control = 0)

3.59 (0.84)

36.08 (7.02, 185.48)

4.29***

25.10***

Number of assignments attempted

0.59 (0.21)

1.81 (1.20, 2.72)

2.85**

8.54**

  1. For instructor, post hoc comparisons with Tukey adjustment for multiple comparisons indicated that instructor 4’s students were more likely to read laterally and make a correct conclusion than instructor 1’s students (p = .028) and instructor 3’s students (p = .033). For problem type, post hoc comparisons with Tukey adjustment for multiple comparisons indicated that students were more likely to read laterally and make a correct conclusion on Fake News than Sourcing Evidence (p < .001), Clickbait Science and Medical Disinformation (p < .001), and Photo Evidence (p = .018). Students were also more likely to read laterally and correctly assess Photo Evidence than Sourcing Evidence (p = .016)
  2. p < .06, *p < .05, **p < .01, ***p < .001
  3. aBaselines set based on the lowest number of problems read laterally and correctly assessed at posttest