Inquiry Learning is meanwhile a core instructional approach within science education. It differs from traditional methods, because  students are required to learn and experience about the “Nature of Science” as they pass through all substantial phases of a research process: These include phases  of developing a research question, formulating hypotheses, planning and performing an experiment, as well as documenting and sharing results (Hamman, 2004; Huber, 2009). There are many examples and ways how to implement Inquiry Learning in the science classroom. There is evidence that such approaches in biology (e.g., by using living animals for observational research) can enhance students’ interest, motivation and positive attitudes towards the topic (Randler, Hummel & Prokop, 2012; Tamir & Shcurr, 1997). Usually, students are guided during the most important steps of inquiry (Hamman, 2004).

Inquiry learning and, subsequently, conducting experiments are an important part of the science education. However, daily practice as well as research reveal that teachers do not include such practices on a regular base. Major reasons are here missing competences of teachers, lack of equipment and laboratories on an organizational level, and too high demands for students and missing self-regulated learning competences. Being able to self-regulate the learning process and have consciousness of one’s own learning process is crucial for inquiry learning (Eckhardt, Urhahne, Conrad, & Harms, 2013). Students are, however, often unable to regulate their learning activities (Azevedo, 2009; Bannert & Mengelkamp, 2013), thus requiring guidance or instruction. Even though students are aware of their own learning strategies, they are often not able to use appropriate learning strategies in the right moment or to use goal-oriented learning strategies (Artelt, 1999; Bannert et al., 2009; Jong & van Joolingen, 1998). 

One possibility to support students’ metacognitive strategies is to foster their learning strategies during the learning phase. Here, this was done by the scaffolding-technique of prompting during biology lessons within a project with working with living bees. In this project students should acquire knowledge about life and development of honey bees and by doing so, learn the basics of scientific research.

Within this study inquiry learning was implemented to foster students understanding of scientific work during four biology lectures. The goal of our study was to investigate the impact of (meta-)cognitive prompts after each unit on learning outcomes and cognitive load. The overall aim of this study was to investigate how students benefit from specific instructional support when implementing inquiry learning in class and how the metacognitive scaffolding by prompts fosters students’ knowledge acquisition.

The research questions were how the scaffolding as applied here fosters knowledge acquisition and conceptual understanding. We assumed that prompting supports learners’ construction of basic knowledge and conceptual understanding of behavioral research methodology here. Furthermore we wanted to examine how students’ motivation and attitude towards living animals affects their knowledge acquisition.

Overall 64 students of the sixth grade (Austrian school system) participated in this experiment. General topics of this intervention included the importance of honeybees for ecological systems and the development and life of bees. The study was conducted using a single-factor experimental research design. A pre-test was used to assess students’ prior knowledge. A post-test was used to analyze the effectiveness of inquiry based learning scenarios combined with the prompting of metacognitive scaffolds. To foster learners’ understanding and to effectively use learning strategies, we designed specific scaffolds for each unit. After working and experimenting with the living bees (at the beehive), we interrupted the unit and had learners to provide answers to pre-given metacognitive prompts (e. g., “Think about the learned information again intensively: What do you remember of the taught lesson today?”). The prompting, which was focused on each unit’s content respectively was given after each session. We assessed students’ cognitive load after each unit with the intrinsic and extrinsic cognitive load scales developed by Leppinks and van den Heuvel (2015; ICL: Cronbach’s alpha from .53 to .89; ECL: Cronbach’s alpha from .76 to .83), students’ use of learning strategies with the LIST questionnaire (Wild & Schiefele, 1994; metacognitive strategies; Cronbachs’ Alpha from .84 to .91), students’ intrinsic as well as extrinsic motivation using the MSLQ (Pintrich, Smith, Garcia & McKeachie, 1991; Cronbach’s alpha from .70 to .83), and the Positive and Negative Affect Schedule (PANAS, Egloff, Schmukle, Burns, Kohlmann & Hock, 2003; Cronbach’s alpha from .50 to .72). Learners’ knowledge acquisition and conceptual understanding has been assessed with a proprietary knowledge pre- and post-test.

A MANCOVA did not show a main effect for prompting (p = 0.237) but a significant main effect for metacognitive strategies (p = 0.000) as well as a significant main effect for students’ intrinsic motivation (p = 0.000) and students’ extrinsic motivation (p = 0.005). A closer look on single effects revealed that prior knowledge had a significant impact on knowledge acquisition (p = 0.029,

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