The Characteristics Of Problem Representation Have Different Influences On False Memory And Error Detection Among Different Abundance Of Disciplinary Domain Knowledge Students

As a kind of knowledge for cognitive resource allotment and informationprocessing monitoring in the disciplinary domain knowledge system, problematiccondition knowledge plays an important role in problem representation and solving.In this present study, the effects of problematic condition knowledge on probleminformation representation were investigated by using the usual mathematicalarithmetic equations and chemical expressions as the experiment materials in order tocontrol the declarative discipline knowledge and cognitive processes knowledge. Thestudy was divided into three parts; the first part was composed of the characteristic ofdifferent abundance of disciplinary domain knowledge learners on mathematicalproblems’ representational levels and its effect on false memory, the affection ofproblematic condition knowledge can be inferred according to these results. Thesecond part tried to carry out a teaching experiment in chemistry which was adaptedby the supplemental strategies and the problematic condition knowledge was a majorcomplement to it. Further effect to the teaching experiment was verified by using anerror detection task to investigate the event-related brain potentials of error processingbetween teaching experiment group and control group in the third part of this study.In Experiment1, the mechanisms of representational levels of students withdifferent abundance of disciplinary domain knowledge were investigated in5categories mathematical arithmetic equations by a ‘study-recognition’ pattern. Theresults showed,(1) Both rich and poor disciplinary domain knowledge groupsproduced the highest error recognition rates when verbatim and gist features weresimilar to the ‘Old target’, and produced the lowest error recognition rates whenverbatim features were significantly different from the ‘Old target’.(2) There weresignificant differences of the error recognition rates in the similar verbatim featurescondition by two groups, presenting the rich group’s was much lower than the poorgroup’s. The results indicate,(1) Both two groups exhibit serial processing withverbatim features preceding gist features when they encode the two features information.(2) Poor group discard gist features because of their interference andextract the recognition clew according to verbatim features, leading to a low correctrecognition rate.(3) The encoding of verbatim features show no interference in gistfeatures processing for rich group, both verbatim and gist features are considered asextraction clew.In Experiment2, the aim of these two sub-experiments was to investigate howcommon and non-common gist features affected false memory among students withdifferent abundance of disciplinary domain knowledge. The DRM paradigm was usedand the results showed,(1) Under the common gist features condition, both twogroups produced higher false alarm rates of critical lures than those in thenon-common gist features condition.(2) The poor group had significantly higher falsealarm rates and longer reaction time on critical lures than rich group in the commongist features condition.(3) Both rich and poor groups produced an inconspicuousdifference between the variation of hit rates under the common and non-common gistfeatures while the variation of false alarm rates of critical lures had. The resultsindicate, the abundance of disciplinary domain knowledge has an influence on falsememory and heighten the clarity of gist features in problem informationrepresentation helps to reduce it. There are two different representation forms of trueand false memories: true semantic memory is activated via phonological informationand easily affected by the abundance of disciplinary domain knowledge, while falsememory is gaining fluency through the semantic information and it is easily affectedby the clarity of visual cues.The third experiment of this research carried out a teaching experiment with theunit of disciplinary domain knowledge in chemistry which was adapted by thesupplemental strategy. Unit text papers of chemistry were used to investigate theeffects of supplemental teaching on students’ academic performances and analyze therelationship between them. The results showed:(1) The group of teaching experimenthad better academic performances than control group.(2) On the contrast of controlgroup, the academic performances of excellent and average students weresignificantly increased, but the variation of poor students’ was inconspicuous. The results indicate: disciplinary domain knowledge supplemental teaching cansignificantly improve students’ academic performances and the students’ existinglevels of knowledge are important factor on the efficiency of supplemental teaching.The aim of the fourth experiment was to investigate the ERP components ofdisciplinary domain knowledge teaching experiment on two kinds of error featuresunder the subjects-based error response detection condition and objects-based errorinformation detection condition. The Go/No-Go paradigm was used and subjects werechosen to participate in this study according to the previous teaching experiment. Theresults showed,(1) In the error response detection condition, the ERN was elicited byexperimental group exhibited a larger negative deflection under gist features errorsthan verbatim features errors, and the control group was in the contrary.(2) In theerror information detection condition, the verbatim features errors elicited significanthigher ERN amplitudes compared to gist features errors in both groups.(3) Both inerror response and error information detection conditions, the ERN amplitudes weremore negative for experimental group compared with control group. The resultsindicate, although the ERN is significantly elicited in both error detection conditions,but their ERN effects are affected by different factors: subjects-based error responsedetection is mainly modulated by the depth of error processing between subjects andobjects-based error information detection is associated with the clarity of errorinformation. ERN reflects a conscious information processing while error detection.