Themes in eLearning

Development of digital fluency scale: Validity and reliability study

2022-11-13T20:52:43GTB Standard Time

Digitally fluent teachers are expected to contribute to the growth of digitally fluent students. The purpose of this study is to develop a valid and reliable Digital Fluency Scale to determine the digital fluency of pre-service teachers. To create an item pool to develop a scale for digital fluency, the opinions of the focus group meeting participants were gathered by a qualitative method. After the pilot implementation of scale, Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were applied. Data were collected from undergraduate students at a state university in Turkey to conduct for EFA (n: 302) followed by CFA (n: 274). The scale structure with 3 factors and 29 items was revealed. The scale explains 54.65% of the total variance. It was concluded that the Chi-square value (χ2 = 1189.10, df = 371, p <0.001) was moderately significant when the fit indices of the model tested with CFA were examined. It is seen that the other fit values for the model are within the acceptable fit value ranges. Higher scores from the scale indicate a high level of digital fluency.

Student-generated texts as features for predicting learning from video lectures: An initial evaluation

2022-11-13T20:52:46GTB Standard Time

The digital trails that students leave behind on e-learning environments have attracted considerable attention in the past decade. Typically, some of these traces involve the production of different kinds of texts. While students routinely produce a bulk of texts in online learning settings, the potential of such linguistic features has not been systematically explored. This paper introduces a novel approach that involves using student-generated texts for predicting performance after viewing short video lectures. Forty-two undergraduates viewed six video lectures and were asked to write short summaries for each one. Five combinations of features that were extracted from these summaries were used to train eight machine learning classifiers. The findings indicated that the raw text feature set achieved higher average classification accuracy in two video lectures, while the combined feature set whose dimensionality had been reduced resulted in higher classification accuracy in two other video lectures. The findings also indicated that the Gradient Boost, AdaBoost and Random Forest classifiers achieved high average performance in half of the video lectures. The study findings suggest that student-produced texts are a very promising source of features for predicting student performance when learning from short video lectures.

Gamified Flipped Learning Environment: Motivation, Engagement and Academic Achievement

2022-11-13T20:59:27GTB Standard Time

The aim of this study was to examine the effect of gamification on the motivation, engagement and academic achievement of students studying in a flipped learning. The study was conducted with a split-plot factorial design. The participants consist of 54 students studying at a state university in Turkey. The students in the experimental and control groups were studied in flipped learning for 12 weeks. In-classroom activities were conducted based on interactive group activities. Out-of-classroom activities were carried out with asynchronous videos, audio recordings, assessment tests, text, and graphic-based course content. Unlike in the control group, gamification was used in the experimental group. Gamification was used in the out-of-classroom component of the flipped learning. Gamification was carried out using a design model that takes into account the characteristics of the target audience. As a result, it was seen that gamification did not have a significant effect on the motivation, engagement, and academic achievement of students in the flipped learning. The most important question raised by this study is whether the difference between a flipped classroom and flipped learning. Another question this study raises is which component of flipped learning is more effective for gamification. Perhaps, if course contents and in-classroom activities are designed effectively, a trigger will not be needed to motivate or engage students.