Towards Computer-Based Tutoring of Help-Seeking Skills
Vincent Aleven
Bruce M. McLaren
Kenneth R. Koedinger
In today’s economic and technological environment, individuals continually face the challenge of acquiring new knowledge and skills. To be successful, people must be “intelligent novices” (Mathan & Koedinger, 2003), able to get up to speed quickly in a new domain. Meta-cognitive skills are often regarded as key to being a good learner (Bransford, Brown, & Cocking, 2000; Palincsar & Brown, 1984; White & Frederiksen, 1998). While these skills are crucial in today’s society, they are addressed insufficiently in the current educational system.
One such meta-cognitive skill is help seeking. The ability to seek help at appropriate times from appropriate sources and to learn from the received help is important simply because it is not possible for the school system to prepare students for all future skill needs. Also, it is often very difficult to learn a new set of skills by oneself, without any help, say, by reading a textbook and doing the exercises, or by searching the Internet and integrating information found in diverse sources. Typically, it is more effective and efficient to selectively enlist the help of a more experienced individual or even to post a query to a specialized forum or mailing list on the Internet (Keefer & Karabenick, 1998). Developmental psychologists view help seeking as a key strategy for developing independent ability and skills (Nelson-LeGall, 1981). A number of studies have shown that individuals who seek help more effectively have better learning outcomes.
However, there is considerable evidence that many individuals do not seek help effectively (Nelson-LeGall, 1987) or avoid seeking help altogether (Ryan, Gheen, & Midgley, 1998; Ryan, Pintrich, & Midgley, 2001). A number of studies have shown that students with greater prior knowledge of a given domain exhibit more effective help-seeking behavior (e.g., Miyake & Norman, 1979; Nelson-Le Gall, 1987; Nelson-Le Gall, Kratzer, Jones, & DeCooke, 1990; Puustinen, 1998). The troubling consequence of this finding is that those students who are most in need of help are the least likely to get it at appropriate times (Karabenick & Knapp, 1988a). There are social barriers to seeking help, such as fear of being seen as incompetent or not getting full credit for task completion (Nelson-LeGall, 1981) and the expectation that one should solve problems independently (VanderMeij, 1988). Other barriers include inaccurate self-assessment, difficulty in judging when it might pay off to persist in trying to solve a task by oneself rather than seek help, and an inability to formulate good questions. Some forms of help require that one reads and understands “technical” text and evaluates how to apply the general knowledge found in textual sources to the problem at hand, which can be challenging. Finally, many students tend to be performance-oriented (e.g., focused on finishing assigned problems) rather than learning-oriented, thus leading to less effective help seeking (Arbreton, 1998; Karabenick, 2003; Ryan & Pintrich, 1997) and learning (Dweck, 1989).
While help seeking has been studied extensively in social contexts, it has been studied only to a very limited degree in the context of computer-based interactive learning environments (ILEs), even though such systems are becoming increasingly commonplace at many levels of education (Aleven, Stahl, Schworm, Fischer, & Wallace,
2003; Karabenick & Knapp, 1988b). By ILEs we mean a broad range of instructional software including for example computer-assisted instruction (CAI, see Eberts, 1997; Gibbons & Fairweather, 1998; Larkin & Chabay, 1992), intelligent tutoring systems, (Corbett, Koedinger, & Anderson, 1997), authentic problem-solving environments (CTGV, 1997; Slotta & Linn, 2000), systems geared towards the adaptive presentation of instructional multi-media materials (Brusilovsky, 2001; Dillon & Gabbard, 1998), and systems focused on guided discovery learning (de Jong & van Joolingen, 1998). The current chapter focuses on help seeking within one particular type of ILE, namely, Cognitive Tutors (Anderson, Corbett, Koedinger, & Pelletier, 1995). These types of systems are designed to support “guided learning by doing.” They offer a rich problem-solving environment, monitor students as they work through problems in this environment, and provide various forms of guidance including hints and feedback. Cognitive Tutors have been proven to be effective in raising students’ test scores in actual classrooms. As of the spring of 2004 they were in use in approximately 1,700 schools nationwide. Thus they are a prime example of a successful technological educational innovation.
While different ILEs are based on very different pedagogical approaches, a feature common to many systems is on-demand help. For example, the Geometry Cognitive Tutor (Aleven & Koedinger, 2002; Koedinger, Corbett, Ritter, & Shapiro,2000), shown in Figure 1, offers two types of on-demand help, in addition to other forms of tutorial guidance such as feedback on students’ stepwise problem solutions. We shall call these two types of help context-sensitive and de-contextual help, reflecting whether or not the help content is tailored, by the system, to the specific learning context . First, at the student’s request, the tutor provides context-sensitive hints with information tailored toward the student’s specific goal within the problem at hand (see the small window
Figure 1:
The Geometry Cognitive Tutor
entitled “Hint” in the middle of Figure 1). Typically, multiple levels of hints are available for any given problem-solving step. Second, the tutor offers de-contextual help in the form of a Glossary window, which the student can use to browse a set of relevant problem-solving principles and to selectively display more information about each (see the window labeled “Glossary” at the bottom-right of Figure 1). Other systems provide similar de-contextual help facilities, as well as a variety of others, for example, hyperlinked textbooks, custom-designed hyperlinked background material (Slotta & Linn, 2000), or links to relevant lecture materials (Mandl, Gr?sel, & Fischer, 2000)1.
1The distinction between context-sensitive and de-contextual help made above does not align neatly with the difference between executive and instrumental help seeking that has long been made in the literature (see, e.g., Nelson-LeGall, 1985). Executive help seeking has been defined as focused mainly on supporting performance or completing a task, whereas instrumental help seeking episodes are concerned with the acquisition of new skills or knowledge. Given that an ILE’s goal is to support learning, ideally, the help facilities of any given ILE would channel students into instrumental help seeking and would not allow executive help seeking, or perhaps allow it only as a last resort, to allow students who get stuck on one step at least to make progress on other steps. The help facilities in the Geometry Cognitive Tutor were designed with these goals in mind. The context-sensitive hints sequences are meant to encourage instrumental help seeking by first presenting hints that explain why the answer is the way it is, before actually giving the answer. However, they do not completely disallow executive help seeking: a student could simply ignore the hint levels that provide explanations and pay attention only to the hints that provide answers. The tutor’s de-contextual help, on the other hand, (i.e., the on-line Glossary of geometry knowledge) never provides answers directly and thus does not seem open to such executive help-seeking strategies. Yet there is a cost: when information is not tailored to the problem-solving step at hand, there is more work to do for the student, which may lower the likelihood that the help-seeking episode will be successful or the likelihood that the student will select this type of help. Ultimately, the type of help that tends to be used
on-demand help is a key feature of many ILEs, it is important to understand to what extent students use it effectively (e.g., to seek help in an instrumental rather than executive manner) and to what extent the proficient use of help facilities helps students learn better. Certainly the literature on help seeking in social contexts, as indicated above, has illustrated the impact of proficient help seeking (or lack thereof) on student learning. On the other hand, researchers in the field of ILEs have only just begun to study help seeking as an important influence on student learning (for a recent overview of the literature, see Aleven et al., 2003). Some studies have provided evidence that the proficient use of the help facilities offered by an ILE can lead to higher learning outcomes (Renkl, 2002; Wood, 2001; Wood & Wood, 1999). For example, Renkl (2002) found that adding on-demand help to a system that presents students examples to study leads to better learning outcomes. Wood and Wood (1999) studied help seeking with a small-scale intelligent tutoring system and found that students with lower prior knowledge tended to have higher learning gains if they used help more frequently.
However, those same studies, as well as others, have presented evidence that students often use the help facilities of ILEs in ways that are not conducive to learning (Mandl, Gr?sel, & Fischer, 2000). For example, Renkl (2002) identified a group of students with low learning gains who did not use help very frequently. Wood and Wood (1999) found that students with lower prior knowledge were the least likely to use help in an adaptive manner. Unfortunately, such students arguably needed help the most. Aleven and Koedinger (2000), in a classroom study involving the Geometry Cognitive Tutor of
more effectively (i.e., in a more instrumental fashion) is an empirical question. Later in the chapter we present data related to that question.
Figure 1, found evidence of widespread help abuse (e.g., over-use of help) and to a lesser degree of help avoidance. One goal of this chapter is to present data from this study, documenting students’ help use with the Geometry Cognitive Tutor. We believe this evidence to be especially compelling, as it comes from actual classroom use of the tutors.
To interpret these results and adequately address the causes of ineffective help seeking in ILEs, it is important to understand both the system’s and the student’s contribution to the problem. With respect to the system’s contribution, it is important to understand the influence on students’ learning of various factors in the design of help systems. Only a small number of studies have been done in this area. These studies found that the effectiveness of on-demand help often depends on the content of the help messages given by the system. For example, in a study in which the subjects tried to learn, by exploration, how to use a simple computer drawing program, Dutke and Reimer (2000) found that explanations of what to do were less effective in supporting learning than explanations of the functioning of the drawing program that the students were trying to master (Dutke and Reimer used the term operative help and function-oriented help, respectively)2.
2 One could view the central question of this study as: “Which type of help is more instrumental, in the Nelson-LeGall (1985) sense, operative help or function-oriented help?” Dutke and Reimer’s results show that in a context of learning software by task-oriented discovery, function-oriented help is more instrumental. We note further that the distinction between operative help and function-oriented help is orthogonal to that made earlier between context-sensitive and de-contextual help. The function-oriented help and operative help used in the Dutke and Reimer study is not context-sensitive in the way that the hints of the Geometry Cognitive Tutor are – that is, neither type of help refers to specific information in the
Similarly, studies of the content of feedback messages given by ILEs (i.e., messages that were given at the system’s initiative rather than the student’s) have shown an effect of such factors as whether the help message draws attention to the students’goals (McKendree, 1990), the degree of interactivity (i.e., the extent to which students are asked to answer questions when receiving system feedback), and whether the help is couched in abstract or concrete terms (Arroyo, Beck, Beal, Wing, & Woolf, 2001; Arroyo, Beck, Woolf, Beal, & Schultz, 2000).
A second goal of this chapter is to present research aimed at understanding how two additional factors related to the help content may have helped shape students’ help-seeking behavior with the Geometry Cognitive Tutor, namely, (1) whether the system’s help messages focus solely on domain-specific skills and knowledge or whether they also mix in advice at the meta-cognitive level, and (2) the number of levels of help given to the students.
In addition to studying how system design may contribute to good or poor help use, it is important to understand the student’s contribution. As mentioned, many factors may contribute to poor help-seeking behavior. Our research focuses on the hypothesis that students would learn more effectively, across a range of domains, if they had better help-seeking skills. From this viewpoint, help seeking is a meta-cognitive skill that must be acquired and that may be open to instruction. This view is consistent with studies that show the success of instructional programs that focus on teaching other types of meta-cognitive skills, such as self-explanation (Bielaczyc, Pirolli, & Brown, 1995),
given problem or explains how a problem-solving principle applies. It is not clear however that greater context-sensitivity would be appropriate in the given discovery learning context.
comprehension monitoring (Palincsar & Brown, 1984), monitoring problem-solving progress (Schoenfeld, 1987), and self-assessment (White & Frederiksen, 1998). In developing instruction on help-seeking skills, we aim to take advantage of the unique qualities of Cognitive Tutors: Given their proven effectiveness in teaching domain-specific skills and knowledge, it is plausible that they could also help students learn to seek help more effectively. We hypothesize that such support for help seeking would help students to learn better at the domain level but also help them to become better help seekers and thus better future learners. The question whether an ILE can be effective in fostering meta-cognitive skills such as help seeking has not, to our knowledge, been addressed in the literature on ILEs. One possible exception, in which some interesting but preliminary results were reported, is the work of Luckin and Hammerton (2002) on “meta-cognitive scaffolding.”
The third goal of this chapter is to present ongoing work aimed at extending the Geometry Cognitive Tutor so that it provides tutoring on students’ help-seeking behavior, in addition to assistance with geometry problem solving. The extension to the tutor, called the Help-Seeking Tutor Agent, will be able to evaluate at any point during a tutoring session whether the student could benefit by asking for help, in light of how difficult the given step is estimated to be at that point in time for that particular student. It will comment when the student makes unnecessary or too-rapid help requests and also when the student refrains from asking for help in situations where it would likely be beneficial. This approach will be implemented within the “model tracing” paradigm that underlies the Cognitive Tutor technology (Anderson et al., 1995). In this paradigm, a tutoring system uses a cognitive model, essentially a simulation model of student
thinking that can be executed on the computer, to monitor students’ individual approaches to problems and provide guidance as needed. For example, the Geometry Cognitive Tutor employs a cognitive model of problem-solving skill in the domain of geometry to monitor students’ solution steps and to provide hints and feedback. Similarly, the Help-Seeking Tutor Agent uses a cognitive model of help seeking to evaluate students’ help-seeking behavior. Thus, a key challenge in creating this tutor is the implementation of a detailed model of adaptive help-seeking behavior. We have created an initial model the shares some traits with models of help seeking that have been presented in the literature on help seeking (Nelson-LeGall, 1981; Newman, 1998) but is considerably more detailed. Further, it is a computational model, meaning that it can be executed on a computer to make (real-time) predictions about help seeking and to provide tutoring.
In summary, we will present data about students’ use of the help facilities of the Geometry Cognitive Tutor and document the difficulties that students have in using help effectively. We then present progress made toward addressing those difficulties with respect to both solution approaches outlined above, including preliminary data investigating the influence of two factors on students’ help use, namely, the mixing of cognitive and meta-cognitive advice, and the number of hint levels. We also present our initial cognitive model of help seeking that will form the basis for extending the Tutor so that it helps students become better help seekers. Finally, we describe an experiment to evaluate whether this tutor actually improves students’ help-seeking ability and whether they learn better as a result.
The Geometry Cognitive Tutor
Cognitive Tutors are a form of intelligent instructional software, designed to help students as they learn a complex cognitive skill (Anderson, et al, 1995). This type of tutoring software provides support for learning by doing in the form of context-sensitive hints, feedback, and individualized problem selection. Carefully integrated with classroom instruction, Cognitive Tutors for high-school algebra and geometry have been shown to be about one standard deviation better than traditional classroom instruction (Koedinger, et al., 1997; 2000) and have also been shown to be instrumental in enhancing student motivation (Schofield, 1995). Currently, Cognitive Tutors for Algebra I, Algebra II, and Geometry are disseminated nationwide by a company spun off from our research group (see http://www/https://www.doczj.com/doc/829817311.html,). As of the 2003-2004 school year, the Algebra I Cognitive Tutor is used in 1,500 schools around the country, the Geometry Cognitive Tutor in 350 schools.
The Geometry Cognitive Tutor?, shown in Figure 1, is an integrated part of a full-year high-school geometry course (Aleven & Koedinger, 2002). Both the tutor and the curriculum were developed by our research group. Following guidelines of the National Council of Teachers of Mathematics (NCTM, 1989), the tutor presents geometry problems with a real-world flavor. In these problems, students are given a description of a problem situation plus a diagram and are asked to calculate unknown quantities such as angle measures, segment measures, the area of 2D shapes, etc. The tutor offers a rich problem-solving environment in which students can work with both a tabular and diagrammatic representation of the problem and get assistance from a symbolic equation solver tutor if their solution requires it.
As students enter the values for the unknown quantities into the table (shown on the left in Figure 1), the tutor provides feedback indicating whether the entry is correct or not. In the Angles unit, the unit of the tutor curriculum dealing with the geometric properties of angles (most of the data presented in this chapter pertain to this unit), students are asked also to provide brief explanations for each numeric answer by indicating which geometry theorem or definition justifies it (e.g., “Triangle Sum”). They can either select explanations from the tutor’s online Glossary, described further below, or they can type the explanation into the tutor’s table. Students are allowed to move on to the next problem only when they provide correct answers and explanations for all steps.
As mentioned, the tutor provides two forms of on-demand help. The tutor’s online Glossary lists important theorems and definitions of geometry and illustrates each with a simple example diagram (Figure 1, center). This type of help is de-contextual: the information that is presented is not tailored to the specific problem that the student is working on. The students can use the Glossary freely as they work with the tutor. The Glossary also functions as a menu from which students can select the reasons that justify their steps, saving them the effort of typing the name of the theorem. Given that the de-contextual help does not directly provide answers, one might regard it as instrumental help as defined by Nelson-LeGall (1985). Ultimately, though, whether this type of help (or any type of help) is instrumental in helping students learn is an empirical question, the answer of which depends not only on the help itself but also on whether and how students use it.
Further, the tutor provides context-sensitive hints at the student’s request with information on how to complete the next step in the given problem (Figure 1, window in the middle of the figure). For each step, between 5 to 8 levels of hints are available,depending on the specific geometry skill involved. Each hint level provides increasingly more specific advice (see Table 1). The hints were designed not just to communicate to the student which problem-solving principle is applicable and how it applies, but also to communicate a strategy for how they might find an applicable principle, if they were not able to recall it from memory. The early hints in each sequence suggest that the student undertake a Glossary search using a cue identified in the problem (e.g., that the problem
Table 1: Example Hint Sequence in the Geometry Cognitive Tutor
Hint Text
General Hint Plan 1.As you can see in the diagram, Angles LGH and TGH
are adjacent angles. Together they form line HI. How
can you use this fact to find the measure of Angle
TGH?
Identify key problem feature (“adjacent angles”)2.Look in the Glossary for reasons dealing with adjacent
angles.
Recommend use of Glossary to look up relevant info 3.Some rules dealing with adjacent angles are
highlighted in the Glossary. Which of these reasons is
appropriate? You can click on each reason in the
Glossary to find out more.
Help reduce Glossary search 4.If two angles form a linear pair, the sum of their
measures is 180 degrees.
Angle TGH and Angle LGH form a linear pair.
Identify relevant problem-solving principle
5.The measure of Angle TGH plus the measure of Angle LGH is equal to 180 degrees.
6.
The measure of Angle TGH is equal to 180 degrees minus the measure of Angle LGH.Discuss how principle can be applied 7.m ∠TGH = 180° - m ∠LGH
involves an isosceles triangle or supplementary angles). An intermediate hint highlights a few potentially relevant geometry rules in the Glossary, in case the student was not successful in determining which rule is applicable. The later hints in each sequence discuss how the rule can be applied to find the targeted angle measure. Each hint sequence “bottoms out” by stating a simple algebraic expression that describes how to find the unknown quantity. In other words, the bottom-out hint typically comes very close to giving students the answer for the current step in the problem. Thus, the hint sequences progress from indirect help (hints, really), to direct help. One might say that the earlier help levels provide instrumental help (Nelson-LeGall, 1985), whereas the last level (the bottom-out hints) provide executive (Nelson-LeGall, 1985), or expedient (Butler, 1998), help. As before, we caution that judgments as to whether a particular type of help is instrumental or are better made after the fact, based on data relating help use and learning outcomes.
Like all Cognitive Tutors (Anderson, et al., 1995; Koedinger, et al., 1997), behind the scene the Geometry Cognitive Tutor uses a cognitive model to monitor students as they solve problems. The cognitive model represents the skills targeted in the instruction as a set of production rules, following the ACT-R theory of cognition and learning (Anderson & Lebière, 1998). An example of such a skill would be applying the triangle sum theorem to calculate an unknown angle in a triangle, given the measures of the other two angles in the triangle. The cognitive model is an executable simulation of student problem solving. That is, the system can run the model to solve problems step by step in the same manner that students must learn. This executable cognitive model is key to the tutor’s ability to monitor and evaluate students’ activities, for which it uses an algorithm
called “model tracing.” When the student attempts to answer a tutor question (e.g., enters a numeric value into the tutor’s table), the system runs the model to find out what steps it would take in the same situation and gives feedback to the student by comparing the student’s solution step to those generated by the model. Similarly, when the student requests a hint, the system runs the model to generate possible steps, selects the best one, and then produces hint text using templates attached to the production rule in the model that are involved in generating that step.
Cognitive Tutors keep track of the student’s knowledge growth over time by means of a Bayesian algorithm called knowledge tracing (Corbett & Anderson, 1995). The algorithm is invoked at each problem-solving step to update the tutor’s estimates of the probability that the student knows the skills involved in that step. Whether the estimate is incremented or decremented depends on whether the student was able to complete the step without errors and hints. The tutor uses the estimated probability of skill mastery to select problems and make pacing decisions on an individual basis. It displays these estimates in a “skillmeter” window, shown at the top right in Figure 1, to inform the students about their progress. Skills for which the tutor’s estimate exceeds a certain threshold (set to .95) are considered to be “mastered” and are “ticked off” in the skillmeter window. Once the student has reached mastery for all skills, the tutor advances her to the next section of the curriculum. Students tend to be quite aware of this advancement criterion and often keep a close eye on their skillmeter window Students’ help-seeking patterns
In this section, we present data about students’ help-seeking behavior while using the Geometry Cognitive Tutor. We assess this behavior by comparing it to reasonable
predictions about that behavior. We also report how various measures of help use correlate with students’ learning outcomes.
Data collection
The data presented in this section were collected during a classroom study whose goal it was to assess the added value of having students explain their problem-solving steps (Aleven & Koedinger, 2002). The participants were assigned to two conditions, each working with slightly different versions of the tutor. Students in the Explanation condition explained their problem-solving steps (i.e., justified their steps by citing the relevant geometry rule, as described above). Students in the Problem-Solving condition used a tutor version that did not require that they explain their steps (i.e., the table in the tutor interface did not have boxes for entering “Reasons”). Since in this chapter we are not primarily interested in the effect of having students explain, we report the results of both conditions together, except where noted.
The study took place in the course of regular instruction with the Geometry Cognitive Tutor in a suburban school in the Pittsburgh area. The study involved the students in two periods of a Geometry Cognitive Tutor course taught by the same teacher and his assistant. The students were mostly 10th-graders, that is, 15 and 16-year olds. A total of 41 students completed the experiment. During the study, about 50% of the time was devoted to classroom and small-group activities. The other 50% of the time the students worked on the tutor’s Angles unit, one of the six units that make up the full-year curriculum of the tutor. The students completed a pre-test and post-test before and after their work on the tutor. These tests included questions similar to those encountered on the tutor and included transfer problems as well. The pre-test and post-test data indicate that
there were significant learning gains, attributable to the combination of work on the tutor and classroom instruction (Aleven & Koedinger, 2002).
As the students worked with the tutor, detailed logs of the student-tutor interactions were collected. The log data were analyzed to explore patterns of students’use of the tutor’s help facilities, that is, the tutor’s context-sensitive hints and the tutor’s (de-contextual) on-line Glossary.
Use of context-sensitive help
We looked at a number of variables reflecting the students’ use of the tutor’s on-demand hints. As mentioned, these hints are context-sensitive: they provide information tailored to the particular problem-solving step that the student is working on. We expected that students, to the extent that they were good help seekers, would request help from the tutor when faced with a step that looked unfamiliar or when they had made an error, as indicated by the tutor’s feedback, and were not sure how to fix it. We predicted further that good help seekers would use the hints deliberately, that is, read them carefully in order to decide whether they now had enough information to try the step with reasonable confidence or whether they needed to look at a more detailed hint. Finally, we expected that the students, as they became more proficient with a given skill, would request less detailed help from the tutor (i.e., would request to see fewer hint levels).
As it turned out, the students used the tutor’s context-sensitive help on 29% of the answer steps and 22% of the explanation steps. By “step” we mean a subgoal in the problem, or equivalently an entry in the tutor’s answer sheet. Students requested to see a hint before their first attempt at answering on 12% of the answer steps and 9% of the explanation steps. We do not have a firm basis for making a numerical prediction as to
what the optimal rate of help use should be. However, it is clear that help use and errors should to some degree be balanced, that is, should be roughly equal. If students made many errors without asking for help, this would not be good. But neither would it be good if students asked for hints very often while making very few errors. In our data, students made one or more errors on 36% of the numeric answer steps and 37% of the reason steps. Thus, while the frequency of help use was somewhat lower than the error frequency, help use and errors seemed reasonably balanced. After all, it is quite likely that some errors are slips that can be fixed quite easily without requiring assistance from the system. On the other hand, the expectation that students, when faced with an unfamiliar step, would not guess an answer but would request help first was not fully borne out. Regardless of the precise criterion one uses for deeming a step to be “unfamiliar,” it seems unlikely that only one out of every 10 steps would be unfamiliar when students were working in a novel domain. As further evidence of help avoidance, the students had a tendency to resist asking for a hint, even after making multiple errors on a given step. Details can be found in Aleven and Koedinger (2000).
We also looked for evidence that the tutor’s help messages helped to improve students’ performance with the tutor, that is, that they made it easier for students to complete tutor problems (see Table 2). Overall, students made fewer errors on answer attempts that followed a hint request than on steps where their first action was an answer attempt (82% correct v. 62% correct). Further, after a student made one or two errors on a step, asking for help as the next action reduced both the number of subsequent errors as well as the time needed to complete the step (Aleven & Koedinger, 2000). Thus, the help messages aided performance. Similar evidence that the use of context-sensitive help in an
intelligent tutoring system aids performance was found in other studies as well (Anderson, Conrad, & Corbett, 1989; McKendree, 1990). It does not necessarily follow however that students’ help use led to more efficient or effective learning. In order to support that conclusion, one would need to compare learning results obtained with tutor versions with and without hints.
Finally, we looked at a number of variables that relate to how deliberately students used the help messages (see Table 3). The students spent one second or less with as much as 68% of the hints at intermediate levels, meaning that their next action after requesting the hint (often this was the next hint request) occurred in less than one second.By “intermediate levels” we mean all levels but the last. Also, students spent an average of 2.3 seconds per intermediate hint, which seems inadequate to read and interpret it and assess whether one knows enough to enter the answer. Further, on 81% of the steps on which students requested hints, they requested to see all hint levels including the bottom-out hint. As mentioned, the tutor’s bottom-out hints stopped just short of handing students the answer. These data point to frequent use of a strategy in which students click their way through all hint levels as quickly as they can until they reach the bottom-out hint. In other words, the majority of the time, the students choose to use the tutor’s context-sensitive hints in (what appears to be) highly executive fashion. This “gaming”
Table 2: The effect of hints on subsequent performance (i.e., performance on answer
attempts immediately following a hint)
%Correct after
intermediate hint
%Correct after bottom-out hint %Correct after any hint %Correct when first action is answer attempt 64%87%82%62%
behavior has been studied in other work with Cognitive Tutors (Baker, Corbett, & Koedinger, 2004).
Summing up the findings with respect to students’ use of the tutor’s context-sensitive hints, while the students appeared to use the tutor’s context-sensitive help with appropriate frequency and while this type of help assisted students in completing the tutor, on closer scrutiny, students’ help use left much to be desired. In particular, the expectation that the students would use the context-sensitive hints in a deliberate manner was not met. Quite the contrary, the students very frequently used hints to get answers quickly, without careful reflection on the answer. In addition, there was evidence that the students avoided hint use at moments in which it would have been appropriate, namely, when faced with unfamiliar steps or after making multiple errors on a step. The observed preoccupation with bottom-out hints is undesirable. In order to learn from being giving the right answer (in this case, the bottom-out hint), one needs to construct an explanation of why the right answer is right (Anderson, et al.,1989). The finding that students focused on the bottom-out hints was not consistent with our expectation that students would need increasingly less detailed help as they became more proficient. The finding is also inconsistent with results from an earlier study with a Cognitive Tutor for Lisp Programming, which showed that the average number of hints requested was 1.5 out of 3 hints (Anderson, personal communication).
Use of de-contextual help
如何写先进个人事迹 篇一：如何写先进事迹材料 如何写先进事迹材料 一般有两种情况：一是先进个人，如先进工作者、优秀党员、劳动模范等；一是先进集体或先进单位，如先进党支部、先进车间或科室，抗洪抢险先进集体等。无论是先进个人还是先进集体，他们的先进事迹，内容各不相同，因此要整理材料，不可能固定一个模式。一般来说，可大体从以下方面进行整理。 (1)要拟定恰当的标题。先进事迹材料的标题，有两部分内容必不可少，一是要写明先进个人姓名和先进集体的名称，使人一眼便看出是哪个人或哪个集体、哪个单位的先进事迹。二是要概括标明先进事迹的主要内容或材料的用途。例如《王鬃同志端正党风的先进事迹》、《关于评选张鬃同志为全国新长征突击手的材料》、《关于评选鬃处党支部为省直机关先进党支部的材料》等。 (2)正文。正文的开头，要写明先进个人的简要情况，包括：姓名、性别、年龄、工作单位、职务、是否党团员等。此外，还要写明有关单位准备授予他(她)什么荣誉称号，或给予哪种形式的奖励。对先进集体、先进单位，要根据其先进事迹的主要内容，寥寥数语即应写明，不须用更多的文字。 然后，要写先进人物或先进集体的主要事迹。这部分内容是全篇材料
的主体，要下功夫写好，关键是要写得既具体，又不繁琐；既概括，又不抽象；既生动形象，又很实在。总之，就是要写得很有说服力，让人一看便可得出够得上先进的结论。比如，写一位端正党风先进人物的事迹材料，就应当着重写这位同志在发扬党的优良传统和作风方面都有哪些突出的先进事迹，在同不正之风作斗争中有哪些突出的表现。又如，写一位搞改革的先进人物的事迹材料，就应当着力写这位同志是从哪些方面进行改革的，已经取得了哪些突出的成果，特别是改革前后的．经济效益或社会效益都有了哪些明显的变化。在写这些先进事迹时，无论是先进个人还是先进集体的，都应选取那些具有代表性的具体事实来说明。必要时还可运用一些数字，以增强先进事迹材料的说服力。 为了使先进事迹的内容眉目清晰、更加条理化，在文字表述上还可分成若干自然段来写，特别是对那些涉及较多方面的先进事迹材料，采取这种写法尤为必要。如果将各方面内容材料都混在一起，是不易写明的。在分段写时，最好在每段之前根据内容标出小标题，或以明确的观点加以概括，使标题或观点与内容浑然一体。 最后，是先进事迹材料的署名。一般说，整理先进个人和先进集体的材料，都是以本级组织或上级组织的名义；是代表组织意见的。因此，材料整理完后，应经有关领导同志审定，以相应一级组织正式署名上报。这类材料不宜以个人名义署名。 写作典型经验材料-般包括以下几部分： (1)标题。有多种写法，通常是把典型经验高度集中地概括出来，一
汉堡港 汉堡港 地理位置 汉堡港位于欧洲中部，优越的地理条件为汉堡港和其区域伙伴港口提供了强大的竞争优势。 汉堡港通过基尔运河能快速便捷地进入整个波罗的海地区，通过高效的水陆运输与德国内地、中欧、东欧紧密地联系在一起。 相比于任何其它欧洲的主要港口，汉堡港与位于德国、斯堪的纳维亚、波罗的海地区、东欧、俄国、澳大利亚、瑞士的主要市场更加接近。这种地理优势意味着更短的运输时间、更环保的物流运输链和更低的运输成本。 汉堡港不仅仅是一个重要的中心港口和运输中心，接近三分之一从这里进出的货物是由汉堡市区产生的，后者是德国最大的贸易和工业城市。与北部地区其他港口相比，这是非常高的本地商品比重。 这同时也显示了位于离70海里中心地区的汉堡港极具吸引力的运输优势。超巨型集装箱船可以进入汉堡港，提供24小时服务。通过海路运输的货物可以快速、环保地从港口腹地贸易区出入，不必动用成本耗费大的陆地运输。 码头：
汉堡——欧洲中心 汉堡港一直是欧洲以及全球外贸运输链条的中心，汉堡是德国和正在兴起的北欧市场的重要门户。众多国际工业、贸易、物流、航运公司都把汉堡当做他们进出口贸易的通道。 国际航运公司如地中海(MSC)、马士基、东方海外( OOCL)、达飞轮船(CMA CGM)、赫伯罗特(Hapag-Lloyd)、汉堡航运(Hamburg Süd)、日本邮船(NYK Line)、商船三井( MOL) 、中远集装箱运输(COSCO)、中海集团、Grimaldi、阳明(Yang Ming) 等都在汉堡开展业务，许多公司还把他们在德国或欧洲的总部办公室设在汉堡。 汉堡物流位置 物流基地汉堡/顶级物流 汉堡是欧洲发展最快、最高效的物流基地。 在汉堡，约5700家物流公司提供了一整套的增值服务——从运输、储藏、加工、质量控制、包装、试运行、配送、货运管理到运输保险、海关放行、结账开发票。他们在世界范围内组织成了一个完整的供应链。 各种工业、贸易公司从这种综合的服务组合中收获到了很多好处。像Airbus , Still, H&M, Olympus 和Beiersdorf多年来一直将汉堡当做增值服务链的中心，此有助于汉堡吸引新的业务。为了持续满足需求，到2015年，汉堡将为感兴趣的投资者提供大约320公顷的物流基地。 汉堡——欧洲最大的铁路港口 自1999年起，汉堡港每年的铁路运输量增长了大约80%，达到了四千万吨。集装箱运输量增长了170%，达到180万个标准箱。现在每天都有超过220辆货运火车进出汉堡港。在德国甚至 欧洲，没有其它任何一个港口可以提供如此密集的铁路货物运输网络。汉堡港期望，到了2015年，每天可以处理450到500辆货运火车。这种大幅度的增长可以通过集装箱运输来保证：在 不久的将来，汉堡港预计可以通过铁路运输处理450万个标准箱。
小学生个人读书事迹简介怎么写800字 书,是人类进步的阶梯,苏联作家高尔基的一句话道出了书的重要。书可谓是众多名人的“宠儿”。历来,名人说出关于书的名言数不胜数。今天小编在这给大家整理了小学生个人读书事迹,接下来随着小编一起来看看吧! 小学生个人读书事迹1 “万般皆下品,惟有读书高”、“书中自有颜如玉,书中自有黄金屋”,古往今来,读书的好处为人们所重视,有人“学而优则仕”,有人“满腹经纶”走上“传道授业解惑也”的道路……但是,从长远的角度看,笔者认为读书的好处在于增加了我们做事的成功率,改善了生活的质量。 三国时期的大将吕蒙,行伍出身,不重视文化的学习,行文时,常常要他人捉刀。经过主君孙权的劝导,吕蒙懂得了读书的重要性,从此手不释卷,成为了一代儒将,连东吴的智囊鲁肃都对他“刮目相待”。后来的事实证明,荆州之战的胜利,擒获“武圣”关羽,离不开吕蒙的“运筹帷幄,决胜千里”,而他的韬略离不开平时的读书。由此可见,一个人行事的成功率高低,与他的对读书,对知识的重视程度是密切相关的。 的物理学家牛顿曾近说过,“如果我比别人看得更远,那是因为我站在巨人的肩上”,鲜花和掌声面前,一代伟人没有迷失方向,自始至终对读书保持着热枕。牛顿的话语告诉我们,渊博的知识能让我们站在更高、更理性的角度来看问题,从而少犯错误,少走弯路。
读书的好处是显而易见的,但是,在社会发展日新月异的今天,依然不乏对读书,对知识缺乏认知的人,《今日说法》中我们反复看到农民工没有和用人单位签订劳动合同,最终讨薪无果;屠户不知道往牛肉里掺“巴西疯牛肉”是犯法的;某父母坚持“棍棒底下出孝子”,结果伤害了孩子的身心,也将自己送进了班房……对书本,对知识的零解读让他们付出了惨痛的代价,当他们奔波在讨薪的路上,当他们面对高墙电网时,幸福,从何谈起?高质量的生活,从何谈起? 读书,让我们体会到“锄禾日当午,汗滴禾下土”的艰辛;读书,让我们感知到“四海无闲田,农夫犹饿死”的无奈;读书,让我们感悟到“为报倾城随太守,西北望射天狼”的豪情壮志。 读书的好处在于提高了生活的质量,它填补了我们人生中的空白,让我们不至于在大好的年华里无所事事,从书本中,我们学会提炼出有用的信息,汲取成长所需的营养。所以,我们要认真读书,充分认识到读书对改善生活的重要意义,只有这样,才是一种负责任的生活态度。 小学生个人读书事迹2 所谓读一本好书就是交一个良师益友,但我认为读一本好书就是一次大冒险,大探究。一次体会书的过程,真的很有意思,咯咯的笑声,总是从书香里散发;沉思的目光也总是从书本里透露。是书给了我启示,是书填补了我无聊的夜空,也是书带我遨游整个古今中外。所以人活着就不能没有书,只要爱书你就是一个爱生活的人,只要爱书你就是一个大写的人,只要爱书你就是一个懂得珍惜与否的人。可真所谓
法国葡萄酒主要葡萄品种介绍 贝露娃（中国称呼为黑比诺）- Pinot Noir 贝露娃是名贵红酒用葡萄的皇后。其酒体温柔清雅，其特点是年轻时清雅芳香，成熟时温柔雅致，果味充盈而复合，并带有较明显的草莓和樱桃的香气。贝露娃可以酿出全世界最令人兴奋的红酒，但美玉有瑕，贝露娃是公认难以栽植的葡萄品种，其果粒虽成熟较早，但脆弱、皮薄、易腐烂。 嘉本纳沙威浓（民国时期开始，中国人也称为赤霞珠）- Cabernet Sauvignon 嘉本纳沙威浓是高贵的红酒葡萄品种之王，在全世界广为种植。其颗粒小、皮厚、晚熟，酿成的酒色泽深浓。葡萄酒浅嫩时单宁酸味激烈，有藏酿之质。其特点是最能表现黑加仑子味，蜜瓜味、甘草味，酒体结构丰厚结实，酒力强劲。
上图为嘉本纳沙威浓（也称为赤霞珠Cabernet Sauvignon） 穗乐仙- Shiraz( Syrah ) 穗乐仙是古典红酒用葡萄中的王子。属中浓度酒体,在嘉本纳沙威浓与贝露娃之间，具藏酿价值。完全成熟时，如上等贝露娃一样质地柔滑而浓郁。穗乐仙是一种晚熟品种，色泽较深，在温暖的土质如花岗岩土壤中生长最佳。但如种植过密，它所特有的桑椹果香和黑胡椒味就会变淡。 上图为穗乐仙，也称为设拉子-Shiraz（Syrah） 梅乐- Merlot 梅乐也是最受欢迎的红葡萄品种。梅乐之所以受欢迎是因为它早熟、鲜嫩且多产，可以用来大量酿制美味而柔滑的葡萄酒。也可以广泛用作与其它葡萄品种混合成成熟平衡的红酒。梅乐在较凉的地方长势良好。
上图为梅乐（Merlot） 佳美- Gamay 佳美原产自法国布根地，现在主要产于宝祖利村。所产葡萄酒颜色呈淡紫红色，单宁含量非常低，口感清淡，富含新鲜果香。用佳美酿制的葡萄酒简单易饮，通常不适宜久存，属于酒龄年轻时饮用的葡萄酒。但若生长在火成页岩、石灰含量少的土质上，佳美也能生产出丰厚浓郁耐久存的红酒，如几个宝祖利村的特级产区Moulin-a-Vent、St. Amour等等。除宝祖利村之外，以卢雅雨河谷种植最多。至于加州产的Gamay Beaujolais是贝露娃（Pinot Noir)的一种，并非真正的佳美种。 添帕尼优- Tempranillo 添帕尼优原产于西班牙北部，字源学上意指“早熟”之意。贫瘠坡地的石灰黏土是其最佳的种植条件，不同于其它西班牙品种，适合较凉爽温和的气候。添帕尼优是里奥哈最重要的品种，主要种植于上里奥哈Rioja Alta和Rioja Alavesa，另外在西班牙北部也普遍种植，但在他国并不著名。添帕尼优的品质不差，酸度不足是其常有的缺点，酿酒有时与其它葡
To Ask or Not to Ask, That Is the Question! 1“Those who can, do. Those who can’t, teach.” This joke is frequently directed against members of the teaching profession. It’s not a very kind comment–but jokes are seldom friendly! It’s probably not intended (usually) to be interpreted literally, however; the speaker is, very likely, making a rather tongue-in-cheek1 comment about the profession, in much the same way that cutting comments are often made about bank managers, lawyers, car salesmen and the like! 2At least, such unkind comments are fairly commonplace in many countries of the English-speaking world; we teachers are fair game2 in the eyes of the general public. We’re fair game too, very often, in the eyes of our students when we teach in schools, colleges or universities in The United Kingdom, The United States, and other countries where English is the first language of the majority of the population. Students and school children frequently behave very disrespectfully towards their teachers in secondary schools; sometimes this disrespect escalates into verbal abuse or even, in extreme cases, physical violence. Some parents even behave in the same way, and support the non-cooperative, sometimes even offensive, behaviour of their offspring towards teachers. 3This type of disrespectful behaviour towards teachers–and, indeed, towards other members of society such as police officers, shopkeepers and the elderly–is a relatively recent phenomenon. Certainly, respect for “figures of authority”as well as for fellow citizens, used to be the norm rather than the exception just a few years ago in my own country, but in recent years it seems that selfish behaviour and arrogant disregard for the rights and the well-being of others is of little or no concern to a sizable number of people who live in the English-speaking world. Fortunately it’s not a case of disrespect and disregard being now the norm, but it does appear nowadays to be less of an exception. 4What about in countries such as this one, where English is not the first language? Have patterns of behaviour changed over the past few years in these countries? Have traditional values been adapted to meet the conditions and challenges of the late twentieth and the just-beginning twenty-first centuries? Have some of these traditional values been eroded3, even? Are they perhaps seen now as irrelevant? 5Here in China, for example, to the outside observer it probably appears that the fundamentals of Chinese behaviour have not changed significantly over the past two or three decades, despite the changes that are clearly visible in the outward appearance of towns and cities in China as a result of massive building and infrastructure projects. Certainly the outside observer who is not Chinese would not be able to detect subtleties of change in, for example, traditional courtesies and forms of respect exhibited between people in their day-to-day exchanges: few foreigners would understand the full significance of such courtesies in the first place, so subtle changes would not even be noticed, let alone understood. But Chinese people themselves would, presumably, be acutely aware of any such changes. Certainly the older generation–the grandfathers and grandmothers–would both notice and understand if the underlying and essential nature and character of today’s youngsters were radically changed. 1tongue-in-cheek: intended to be humorous and not meant seriously 2 fair game: if someone or something is fair game, it is acceptable, reasonable, or right to criticize them 3 erode: to gradually reduce the strength or importance of something, or to be gradually reduced in this way
葡萄品种介绍 葡萄品种Chardonnay霞多丽Sauvignon Blanc 长相思 葡 萄 园 中 葡萄特征果粒大，呈黄色，边缘带棕色斑点 萌芽早，早熟，有高糖潜力（高酒精度），容 易种植，适应能力强，产量高 中等大小果粒，果串紧凑（不通风，容易霜霉菌）， 高酸度，萌芽晚，早熟，特别茂盛。 容易感染白粉霉，霜冻，晚季时酸度下降孢菌，白粉霉，黑霉 气候适合多种气候，在温暖环境中会成熟过快适应凉爽气候 土壤适合多种土壤，最适合石灰质土壤（碱性土 壤），石灰石，白垩土，砂石。 不适合潮湿或肥沃的土壤 白垩土，沙烁，粘土，燧石（火石），泥灰土 酒 厂 中 苹果酸乳酸 发酵 被广泛应用，添加黄油质感，奶油未：保持清爽的酸度和辛辣的香味（植物香气） 发酵：口感柔和（西班牙，智利）调配调配：添加塞美容，柔和口感和增添香味（波尔 多产区，有很强的陈年能力）橡木熟成与橡木接触，加深颜色，带有烤面包木材味添加烤面包的风味，使香气变得柔和。 塞美容Semillon+长相思 惰性容器熟 成 保留矿物质和水果特征保持新鲜的香气 窖藏能力大部分出厂后饮用，顶级酒可窖藏10+年大部分年轻时饮用苏玳出产的可窖藏数几十年。 主要著名产区法国勃艮第（夏布利Chablis，默尔索 Meursault，布衣富塞Pouill-Fuisse），香槟产区 Champagne 法国卢瓦尔河（桑塞尔Sancerre，布衣富美 Pouillu-Fume）清爽，无橡木风格。 法国波尔多（苏玳Sauternes）贵腐甜酒。经常与 塞美容调配，橡木风格 美国加州California：浓郁，橡木风格 澳大利亚Australia：热带水果，橡木风格 新西兰（马尔伯勒Mrlborough）清爽，无橡木风 格。 智利Chile，阿根廷Argentina，新西兰New Zealand，南非South Africa，俄勒冈州Oregon 智力：非常辛辣的香气 加州：有时候标为：Fume Blanc 南非South Africa，澳大利亚Australia 外观 Appearance 中等稻草黄/绿色 中等到深金/黄色(用过橡木桶) 浅等稻草黄/绿色
个人先进事迹简介 01 在思想政治方面,xxxx同学积极向上,热爱祖国、热爱中国共产党,拥护中国共产党的领导.利用课余时间和党课机会认真学习政治理论,积极向党组织靠拢. 在学习上,xxxx同学认为只有把学习成绩确实提高才能为将来的实践打下扎实的基础,成为社会有用人才.学习努力、成绩优良. 在生活中,善于与人沟通,乐观向上,乐于助人.有健全的人格意识和良好的心理素质和从容、坦诚、乐观、快乐的生活态度,乐于帮助身边的同学,受到师生的好评. 02 xxx同学认真学习政治理论,积极上进,在校期间获得原院级三好生,和校级三好生,优秀团员称号,并获得三等奖学金. 在学习上遇到不理解的地方也常常向老师请教,还勇于向老师提出质疑.在完成自己学业的同时,能主动帮助其他同学解决学习上的难题,和其他同学共同探讨,共同进步. 在社会实践方面,xxxx同学参与了中国儿童文学精品“悦”读书系,插画绘制工作,xxxx同学在班中担任宣传委员,工作积极主动,认真负责,有较强的组织能力.能够在老师、班主任的指导下独立完成学院、班级布置的各项工作. 03 xxx同学在政治思想方面积极进取,严格要求自己.在学习方面刻苦努力,不断钻研,学习成绩优异,连续两年荣获国家励志奖学金；作
为一名学生干部,她总是充满激情的迎接并完成各项工作,荣获优秀团干部称号.在社会实践和志愿者活动中起到模范带头作用. 04 xxxx同学在思想方面,积极要求进步,为人诚实,尊敬师长.严格 要求自己.在大一期间就积极参加了党课初、高级班的学习,拥护中国共产党的领导,并积极向党组织靠拢. 在工作上,作为班中的学习委员,对待工作兢兢业业、尽职尽责 的完成班集体的各项工作任务.并在班级和系里能够起骨干带头作用.热心为同学服务,工作责任心强. 在学习上,学习目的明确、态度端正、刻苦努力,连续两学年在 班级的综合测评排名中获得第1.并荣获院级二等奖学金、三好生、优秀班干部、优秀团员等奖项. 在社会实践方面,积极参加学校和班级组织的各项政治活动,并 在志愿者活动中起到模范带头作用.积极锻炼身体.能够处理好学习与工作的关系,乐于助人,团结班中每一位同学,谦虚好学,受到师生的好评. 05 在思想方面,xxxx同学积极向上,热爱祖国、热爱中国共产党,拥护中国共产党的领导.作为一名共产党员时刻起到积极的带头作用,利用课余时间和党课机会认真学习政治理论. 在工作上,作为班中的团支部书记,xxxx同学积极策划组织各类 团活动,具有良好的组织能力. 在学习上,xxxx同学学习努力、成绩优良、并热心帮助在学习上有困难的同学,连续两年获得二等奖学金. 在生活中,善于与人沟通,乐观向上,乐于助人.有健全的人格意 识和良好的心理素质.
PECVD工序段学习汇报
目录 1.PECVD设备概况 2.工作流程介绍 3.工艺步骤介绍 4.工艺配方的学习 5.常见的异常及原因
1. CentrothermPECVD 设备概况 Centrotherm 设备的基本功能单元包括：硅片装载区域、热风排风柜、炉体、气体系统、真空系统；同时，在装载区域配备了垂直层流系统，用于净化空气，设备的简要示意图如下图所示： 俯视图 平视图 2.工作流程介绍 操作控制单元 硅片装载区 炉体 特气柜
在CVD 工艺中用一部推车来手动将工艺舟移入设备中进行加 工，以及在加工结束后将工艺舟移除设备，推车锁定在设备中用作加工后冷却工艺舟的存放处。 （1）当一个工艺结束，那个炉管的软着陆系统（SiC 桨）会进入石英管中，把装有镀过膜硅片的石墨舟取出；（2）提升系统会将石墨舟从SiC 上取下，放入存储位置，进行冷却，同时滑轨会把一个新 工艺舟用作来在热化学工艺过程中作为硅片的机械承载器，为石墨舟。
装满的石墨舟由硅片装载系统送入石墨舟装载位置；（3）提升系统会将新装满的石墨舟送到SiC桨上；（4）软着陆系统会把石墨舟送入石英管，然后桨退出，关闭炉门，工艺开始允许；（5）之后，提升系统把刚刚在存储位置冷却的石墨舟送到滑轨上，由滑轨送到外界的自动硅片装载系统中。 全自动硅片装载系统，通过石墨舟传输系统可以把石墨舟送到自动化系统中，包括以下组件：石墨舟提升、石墨舟存储、石墨舟传输系统。 3.工艺步骤介绍 1. 工艺开始（processing started ） 2. 充氮（fill tube with N2） 3. 桨在高位进舟loading boat (paddle in upper position) 4. 桨降至低位paddle moves downwards 5. 桨在低位移出管外move out (paddle in lower position ) 6. 管内抽真空并作压力测试（evacuate tube and pressure test）
一、解题步骤 第一步，快速浏览题目。划出标志词或关键词，对5个题目有大概印象以便阅读时有侧重点。一般来说，对于本身已经明确其考查内容的题目，标志词和关键词是比较容易找到的，只看一下题干即可，而对于那些并没有出现标志词和关键词的题目，如：The author suggests that，可以在解答试题时浏览选项作出解答。 第二步，通读文章 首先阅读第一段，因为第一段通常会告诉我们作者将要讨论的话题。然后阅读下面各段的第一句话，以对每个段落的内容有大概的了解，然后再阅读最后一段，以帮助我们对文章内容进行概括，或了解作者的评价、态度等。在阅读的过程中不用过于注重词句的把握，遇到不认识的单词不必作太久的停留，以免影响阅读速度。 第三步，解答试题 根据试题中的标志词和关键词，找到试题在文章中对应的句子，并对其进行仔细阅读，然后对比四个选项，选出正确答案。但要注意解题时要看作者在文中用了什么样的口气。若用褒义词，显然是赞成；若用贬义词，显然是反对；若客观陈述，则是中性的立场。更为明显的一个解题办法，就是寻找文中的转折词，一般转折此后面的文段表明了作者的观点。
三、题型分类 在大学英语四级考试中，阅读理解的试题类型可以分为以下五大类：主旨题、细节题、语义题、推理题和观点态度题。 1.细节题：四级考试阅读理解中出现频率最高的就是客观事实细节类试题。事实或细节是文章中用来论证或说明主题的依据。这类问题不掺杂主观内容，而是针对文章的某个具体细节，如：时间、地点、人物、原因、结果、条件、现象等的提问。细节题主要对文中具体事实和细节进行提问。有时候，这类题目会进一步演化为是非判断题（true or false)，考查我们的辨别和排除能力。。这类题的提问方式一般为：When (Where, Who, Why, What, Ho w)…? All of the following are mentioned in the passage except… The author says…because… Which of the following may be the best reason for… 【解题技巧】 在做细节题时，首先应当仔细阅读题目，弄清题目的具体要求。通常细节题的答案在文章中都会找到，但是，往往照抄原文的句子并不一定是正确选项,正确答案应该是与原文意思和所问问题相符的才对(即答案的表述和原文会有所差别，常常不是文章中的原话，而是词语或句子的同义表达)。关键词的确定也有技巧。如果题目或选项中有专有名词（人名、
优秀党务工作者事迹简介范文 优秀党务工作者事迹简介范文 ***，男，198*年**月出生，200*年加入党组织，现为***支部书记。从事党务工作以来，兢兢业业、恪尽职守、辛勤工作，出色地完成了各项任务，在思想上、政治上同党中央保持高度一致，在业务上不断进取，团结同事，在工作岗位上取得了一定成绩。 一、严于律己，勤于学习 作为一名党务工作者，平时十分注重知识的更新，不断加强党的理论知识的学习，坚持把学习摆在重要位置，学习领会和及时掌握党和国家的路线、方针、政策，特别是党的十九大精神，注重政治理论水平的提高，具有坚定的理论信念;坚持党的基本路线，坚决执行党的各项方针政策，自觉履行党员义务，正确行使党员权利。平时注重加强业务和管理知识的学习，并运用到工作中去，不断提升自身工作能力，具有开拓创新精神，在思想上、政治上和行动上时刻同党中央保持高度一致。 二、求真务实，开拓进取 在工作中任劳任怨，踏实肯干，坚持原则，认真做好学院的党务工作，按照党章的要求，严格发展党员的每一个步骤，认真细致的对待每一份材料。配合党总支书记做好学院的党建工作，完善党总支建设方面的文件、材料和工作制度、管理制度等。
三、生活朴素，乐于助人 平时重视与同事间的关系，主动与同事打成一片，善于发现他人的难处，及时妥善地给予帮助。在其它同志遇到困难时，积极主动伸出援助之手，尽自己最大努力帮助有需要的人。养成了批评与自我批评的优良作风，时常反省自己的工作，学习和生活。不但能够真诚的指出同事的缺点，也能够正确的对待他人的批评和意见。面对误解，总是一笑而过，不会因为误解和批评而耿耿于怀，而是诚恳的接受，从而不断的提高自己。在生活上勤俭节朴，不铺张浪费。 身为一名老党员，我感到责任重大，应该做出表率，挤出更多的时间来投入到**党总支的工作中，不找借口，不讲条件，不畏困难，将总支建设摆在更重要的位置，解开工作中的思想疙瘩，为攻坚克难铺平道路，以支部为纽带，像战友一样团结，像家庭一样维系，像亲人一样关怀，践行入党誓言。把握机遇，迎接挑战，不负初心。
主要事迹简介怎么写 概括?简要地反映?个单位(集体)或个?事迹的材料。简要事迹不?定很短，如果情况 多的话，也有?千字的。简要事迹虽然“简要”，但切忌语?空洞，写得像?学?期末鉴定。 ?应当以事实来说话。简要事迹是对某单位或个?情况概括?简要地反映情况，?如有三个??很突出，就写三个??，只是写某???时，要把主要事迹突出出来。 简要事迹?般来说，?少要包括两个??的内容。?是基本情况。简要事迹开头，往往要??段?字来表述?些基本情况。如写?个单位的简要事迹，应包括这个单位的?员、 承担的任务以及?段时间以来取得的主要成绩。如写个?的简要事迹，应包括该同志的性 别、出?年?、参加?作时间、籍贯、民族、?化程度以及何时起任现职和主要成绩。这 样上级组织在看了材料的开头，就会对这个单位或个?有?个基本印象。?是主要特点。 这是简要事迹的主体部分，最突出的事例有?个??就写成?块，并按照?定的逻辑关系进 ?排列，把同类的事例排在?起，?个??通常由?个?然段或?个?然段组成。 写作时，特别要注意以下四点： 1.?第三?称。就是把所要写的对象，是集体的?“他们”来表述，是个?的称之为“他(她)”。 (她)”，单位可直接写名称，个?可写其姓名。 为了避免连续出现?个“他们”或“他 2.掌握好时限。?论是单位或个?的简要事迹，都有?个时间跨度，既不要扯得太远，也不 要故意混淆时间概念，把过去的事当成现在的事写。这个时间跨度多长，要根据实际情况 ?定。如上级要某个同志担任乡长以来的情况就写他任乡长以来的事迹;上级要该同志两年 来的情况，就写两年来的事迹。当然，有时为了需要，也可适当地写?点超过这个时间的 背景情况。 3.?点他?的语?。就是在写简要事迹时，可?些群众的语?或有关?员的语?，这样会给??种?动、真切的感觉，衬托出写作对象?较?的思想境界。在?他?语?时，可适当加?，但不能造假。 4.?事实说话。简要事迹的每?个??可分为多个层次，?个层次先??句话作为观点，再???两个突出的事例来说明。?事实说话时，要尽量把?个事例说完整，以给?留下深 刻印象。
第27卷第3期唐山师范学院学报2005年5月Vol. 27 No.3 Journal of Tangshan Teachers College May 2005 奈达翻译理论初探 尹训凤1，王丽君2 （1.泰山学院外语系，山东泰安 271000；2.唐山师范学院教务处，河北唐山 063000） 摘要：奈达的翻译理论对于翻译实践有很强的指导作用：从语法分析角度来讲，相同的语法结构可能具有完全不同的含义；词与词之间的关系可以通过逆转换将表层形式转化为相应的核心句结构；翻译含义是翻译成败的关键所在。 关键词：奈达；分析；转换；重组；核心句 中图分类号：H315.9 文献标识码：A 文章编号：1009-9115（2005）03-0034-03 尤金?奈达是美国当代著名翻译理论家，也是西方语言学派翻译理论的主要代表，被誉为西方“现代翻译理论之父”。他与塔伯合著的《翻译理论与实践》对翻译界影响颇深。此书说明了中国与西方译界人士思维方式的巨大差别：前者是静的，崇尚“信、达、雅”，讲究“神似”，追求“化境”；后者是动的，将语言学、符号学、交际理论运用到翻译研究当中，提倡“动态对等”，注重读者反应。中国译论多概括，可操作性不强；西方译论较具体，往往从点出发。他在该书中提到了动态对等，详细地描述了翻译过程的三个阶段：分析、转换和重组，对于翻译实践的作用是不言而喻的。笔者拟结合具体实例，从以下角度来分析其理论独到之处。 一 一般来说，结构相同的词组、句子，其语法意义是相同或相近的。然而奈达提出，同样的语法结构在许多情况下可以有不同的含义。“名词+of+名词”这一语法结构可以对此作最好的阐释。如下例： （1）the plays of Shakespeare/ the city of New York/ the members of the team/ the man of ability/ the lover of music/ the order of obedience/ the arrival of the delegation 在以上各个词组中，假设字母A和B分别代表一个名词或代词，它们之间存在着不同的关系。在the plays of Shakespeare 中，Shakespeare是施事，plays是受事，用公式表示就是“B writes A”；在the city of New York中，city和New York是同位关系，用公式表示就是“A is B”；the members of the team中，members和team是所属关系，即“A is in the B”；在the man of ability中，“B is A’s characteristic”；在the lover of music中，lover表示的是活动，即动作，music是它的受事，因此可以理解为（he/she）loves the music, 用公式表示就是“X does A to B”（X施A于B）或“B is the goal of A”（B为A的受事）；在the order of obedience中，obedience表示的是活动，order是它的受事，因此用公式表示就是“X does B to A”（X施B于A）或“A is the goal of B”（A为B的受事）；在the arrival of the delegation中，arrival表示动作，而delegation是动作的发出者，所以是“B does A”。 因此它们的结构关系如下所示： the plays of Shakespeare——Shakespeare wrote the plays. the city of New York——The city is New York. the members of the team——The members are in the team. the man of ability——The man is able. the lover of music——(He/She) loves the music. the order of obedience——(People) obey the order. the arrival of the delegation——The delegation arrives. ────────── 收稿日期：2004-06-10 作者简介：尹训凤（1976-），女，山东泰安人，泰山学院外语系教师，现为天津外国语学院研究生部2003级研究生，研究方向为翻译理论与实践。 - 34 -
TRA设备介绍 交换代维张一博 一、引言 在日常维护中，我们经常需要对TRA进行故障处理和调整。故障处理方面我们常用的定位方法是查看告警，拨打测试等，这些方法对显性故障处理比较有效，但如果遇到一些隐性故障就难以定位。本文详细的介绍TRA设备的调整方法和简单介绍通过TEST SYSTEM来进行故障定位。 二、 TRA简介 1、TRA工作原理简介: TRA（Transcoder and Rate Adaptor码率适配器）是BSC的一种基本设备，主要负责将A接口的64k和Abis接口16kbps/8kbps上的语音编码进行相互转换，以及信令的速率适配。常见的TRA有全速率(Full Rate)，加强型全速率(Enhanced Full Rate)和半速率(Half Rate)三类。 BTS
从RBS过来的信号是通过ETC->GS->TRH->SRS->TRA->GS->ETC->MSC，来实现速率转换的。这里需要注意的是SRS，爱立信的设备无法处理低于16kbit/s的速率，而在实际中，为了解决紧张的传输资源，增加传输的使用率，配置了半速率，传送的速率只有8kbit/s,所以要通过SRS处理成16KBIT/S。再转换成64kbit/s的速率。 2、TRA设备类型介绍： TRA有增强型全速率(Enhanced Full Rate)、全速率(Full Rate)和半速率(Half Rate)三种类型。其中增强型全速率为15.1KBIT/S，全速率为13KBIT/S，半速率为6.5KBIT/S。TRA设备对应的设备类型如下图所示： TRA设备使用TRA POOL来动态管理所有的Channel Rate和Speech Version，不同的TRA硬件版本可以在同一POOL中使用。在BYB810设备中，EFR、FR、HR之间的区分是以CHRATE(Channel Rate)和SPV(Speech Version)来区分的。如果CHRATE为HR、SPV=1则为半速率；如果CHRATE为FR，SPV=1时为全速率，SPV=2时为增强型全速率。 R4的版本,每一个框有16个SNT，每个SNT32个设备，可以用到的设备数为24个，其中半速率和加强型全速率是两块板合成一个SNT，FR是一块板为一个SNT, HR和EFR只有8个EM，FR有16个EM。调整的时候，R4版本的需要调整硬件,地址插头,终止插头,选组线都需要调整，需要到现场。R5和R6，只需要在软件上改动就可以。而且R4版本的只能一框一框的调，R5和R6的可以随意调整.R5版本中每个SNT有32个设备，可以用到的设备数为
树立榜样的个人事迹简介怎么写800字 榜样是阳光,温暖着我们的心;榜样如马鞭,鞭策着我们努力奋斗;榜样似路灯,照亮着我们前进的方向。今天小编在这给大家整理了树立榜样传递正能量事迹作文,接下来随着小编一起来看看吧! 树立榜样传递正能量事迹1 “一心向着党”,是他向着社会主义的坚定政治立场;“人的生命是有限的,可是,为人民服务是无限的,我要把有限的生命投入到无限的为人民服务中去”,是他的至理名言;“甘学革命的“螺丝钉”,是他干一行爱一行、钻一行的爱岗敬业态度。他——雷锋,是我们每一个人的“偶像”…… 雷锋的事迹传遍大江南北,他,曾被人们称为可敬的“傻子”。一九六零年八月,驻地抚顺发洪水,运输连接到了抗洪抢险命令。他强忍着刚刚参加救火工作被烧伤的手的疼痛,又和战友们在上寺水库大坝连续奋战了七天七夜,被记了一次二等功。望花区召开了大生产号召动员大会,声势很大,他上街办事,正好看到这个场面,他取出存折上在工厂和部队攒的200元钱,那时,他的存折上只剩下了203元,就跑到望花区党委办公室要为之捐献出来,为建设祖国做点贡献,接侍他的同志实在无法拒绝他的这份情谊,只好收下一半。另100元在辽阳遭受百年不遇洪水的时候,他捐献给了正处于水深火热之中的辽阳人民。在我国受到严重的自然灾害的情况下,他为国家建设,为灾区捐献出自已的全部积蓄,却舍不得喝一瓶汽水。就这样,他毫不犹豫的捐出了自己的所有积蓄,不求功名,不求名利,只求自己心安理得,只求为
革命献出自己的微薄之力,甘愿做革命的“螺丝钉”——在一次施工任务中,他整天驾驶汽车东奔西跑,很难抽出时间学习,他就把书装在挎包里,随身带在身边,只要车一停,没有其他工作时,就坐在驾驶室里看书。他曾经在自己的日记中写下这样一段话：”有些人说工作忙,没时间学习,我认为问题不在工作忙,而在于你愿不愿意学习,会不会挤时间来学习。要学习的时间是总是有的,问题是我们善不善于挤,愿不愿意钻。一块好好的木板,上面一个眼也没有,但钉子为什么能钉进去呢?这就是靠压力硬挤进去的。由此看来,钉子有两个长处：一个是挤劲,一个是钻劲。我们在学习上也要提倡这种”钉子“精神,善于挤和钻。”这就是他,用自己的实际行动来证明自己,用自己的亲生经历来感化世人,用自己的所作所为来传颂古今……人们都拼命地学习他的精神,他的精神被不同肤色的人所敬仰。现在,一切都在变,但是,那些决定人类向前发展的基本要素没有变,那些美好的事物没有变,那些所谓的“螺丝钉”精神没有变——而这正是他的功劳,是他开启了无私奉献精神的大门,为后人树立了做人的榜样…… 这就是他,一位中国家喻户晓的全心全意为人民服务的楷模,一位共产主义战士!他作为一名普通的中国人民解放军战士,在他短暂的一生中却助人无数。而且,伟大领袖毛泽东主席于1963年3月5日亲笔为他题词：“向雷锋同志学习”。 正是因为如此,全国刮起了学习雷锋的热潮。雷锋已经离开我们很长时间了。但是雷锋的精神却深深地在所有中国人心中扎下了根,现在它已经长成一株小树。正以其顽强的生命力,茁壮成长。我坚信,