Generating Topic Headings During Reading of Screen-Based Text Facilitates Learning of Structural Knowledge and Impairs Learning of Lower-Level Knowledge

Abstract

This investigation considers the effects of learner-generated headings on memory. Participants (N = 63) completed a computer-based lesson with or without learner-generated text topic headings. Posttests included a cued recall test of factual knowledge and a sorting task measure of structural knowledge. A significant disordinal interaction was observed with the no headings group performing better on the cued recall test and worse on the structural knowledge sorting task. In addition, a measure of structural knowledge using a list-wise rating task was field trialed. The two structural knowledge tasks were analyzed using a Pathfinder network scoring technique that measured both linear and nonlinear text subtopic organization. The sorting and rating tasks were differentially sensitive to participants' linear and nonlinear knowledge organization. Unexpectedly, the sorting and rating posttest tasks improved cued recall posttest scores. The implications of the results for measuring structural knowledge are considered and suggestions for further studies are presented.Generative learning approaches are strategies that encourage learners to actively consider the relationships among lesson information elements and between lesson information and personal knowledge (Jonassen,

The Effects of Lesson Screen Background Color on Declarative and Structural Knowledge

“…This present investigation replicates our previous research on the effects of lesson background color on recognition and cued recall declarative knowledge, and extends those studies by including the posttest measure of structural knowledge from Clariana and Marker (2007). In addition, color is included or not at posttest in order to consider a lesson-posttest color "matching" alternate hypothesis.…”

“…An individual's structural knowledge has an effect on other measures of learning that may be positive, neutral, or negative depending on how the memory organization relates to the other measures of learning. For example, more coherent knowledge structure is believed to be important for higher-order learning outcomes such as forming inferences, comprehension, and problem solving (Jonassen & Wang, 1992) but has unanticipated and sometimes negative effects on lower-order learning outcomes (Clariana & Marker, 2007). Thus, besides the possible effects of background color hues on declarative knowledge, we are even more interested in context effects on knowledge structure, specifically the organization of the lesson content in the participant's memory.…”

“…How can memory organization that might result from the lesson topic color scheme be measured? Clariana and Marker (2007) used a computer-based sorting task called ALA-Mapper to measure the effects of learner-generated lesson headings on knowledge structure. They proposed that memory of related lesson topics will be more often clustered together for participants who generate lesson headings relative to those who do not.…”

Effectiveness of Structural Feedback Provided by Pathfinder Networks

“…A number of techniques found to be successful have encouraged students to engage in relational, as opposed to proposition-specific, processing in order to determine the structure of studied material. For example, having students create concept maps (Zelik, Schau, & Mattern, 1999) and generate headings for sections of text (Clariana & Marker, 2007) have both been shown to enhance attainment of structural knowledge. Beasley and Waugh (1996) found that simply telling students before studying that they would later be required to create a representation of the organization of the studied material led to greater structural knowledge acquisition relative to a group of students who were not told of the requirement.…”

“…In the present study, we asked students to rate the relatedness of concepts using a rating scale (as in Goldsmith & Johnson, 1990). However, students might alternatively be provided with a set of concepts and asked to sort them (Clariana & Marker, 2007), use them to create a concept map (Clariana, Koul, & Salehi, 2006), or write an essay about them (Clariana & Wallace, 2007). Whichever technique is used, the end result is a matrix of "proximities" (i.e., relatedness) among domain concepts.…”